Genetic polymorphisms associated with coronary events and drug response, methods of detection and uses thereof

ABSTRACT

The present invention provides compositions and methods based on genetic polymorphisms that are associated with coronary heart disease (particularly myocardial infarction), aneurysm/dissection, and/or response to drug treatment, particularly statin treatment. For example, the present invention relates to nucleic acid molecules containing the polymorphisms, variant proteins encoded by these nucleic acid molecules, reagents for detecting the polymorphic nucleic acid molecules and variant proteins, and methods of using the nucleic acid molecules and proteins as well as methods of using reagents for their detection.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. non-provisionalapplication Ser. No. 15/150,636, filed May 10, 2016, which is acontinuation application of U.S. non-provisional application Ser. No.13/929,136, filed on Jun. 27, 2013, which is a continuation applicationof U.S. non-provisional application Ser. No. 13/407,501, filed on Feb.28, 2012, which is a divisional application of U.S. non-provisionalapplication Ser. No. 12/569,475, filed Sep. 29, 2009 (issued as U.S.Pat. No. 8,148,070 on Apr. 3, 2012), which is a divisional applicationof U.S. non-provisional application Ser. No. 12/077,935, filed Mar. 21,2008 (issued as U.S. Pat. No. 7,695,916 on Apr. 13, 2010), which claimspriority to U.S. provisional application Ser. No. 60/919,885, filed onMar. 22, 2007, the contents of each of which are hereby incorporated byreference in their entirety into this application.

FIELD OF THE INVENTION

The present invention is in the field of coronary heart disease (CHD),particularly myocardial infarction (MI), as well as aneurysm/dissectionand drug response, particularly response to statin treatment. Inparticular, the present invention relates to specific single nucleotidepolymorphisms (SNPs) in the human genome, and their association withCHD, aneurysm/dissection, and/or variability in responsiveness to statintreatment (including preventive treatment) between differentindividuals. The SNPs disclosed herein can be used as targets for thedesign of diagnostic reagents and the development of therapeutic agents,as well as for disease association and linkage analysis. In particular,the SNPs of the present invention are useful for identifying anindividual who is at an increased or decreased risk of developing CHD(particularly MI) and aneurysm/dissection, for early detection of thedisease, for providing clinically important information for theprevention and/or treatment of CHD and aneurysm/dissection, forpredicting the seriousness or consequences of CHD andaneurysm/dissection in an individual, for determining the prognosis ofan individual's recovery from CHD and aneurysm/dissection, for screeningand selecting therapeutic agents, and for predicting a patient'sresponse to therapeutic agents such as evaluating the likelihood of anindividual responding positively to statins, particularly for thetreatment or prevention of CHD (such as MI) and aneurysm/dissection. TheSNPs disclosed herein are also useful for human identificationapplications. Methods, assays, kits, and reagents for detecting thepresence of these polymorphisms and their encoded products are provided.

BACKGROUND OF THE INVENTION

Coronary Heart Disease (CHD), Aneurysm/Dissection, and Response toStatin Treatment

The present invention relates to SNPs that are associated with theoccurrence of coronary heart disease (CHD), particularly myocardialinfarction (MI), as well as aortic aneurysm and dissection. The presentinvention also relates to SNPs that are associated with variabilitybetween different individuals in their response to treatment (includingpreventive treatments) with statins (e.g., pravastatin, atorvastatin,etc.), particularly for treatment or prevention of CHD andaneurysm/dissection.

CHD is defined in the Framingham Heart Study as encompassing MI, anginapectoris, coronary insufficiency (which is manifested as ischemia, thatis, impaired oxygen flow to the heart muscle), and coronary heartdisease death. Wilson et al., Circulation 97:1837-1847 (1998). CHD issometimes recorded through clinical records that indicate the followinginterventions: coronary artery bypass graft, angioplasty and stentplacement, in addition to clinical records of MI, angina, or coronarydeath.

As used herein, CHD is defined in accordance with how this term isdefined in the Framingham Heart Study (i.e., as encompassing MI, anginapectoris, coronary insufficiency, and coronary heart disease death), andmay also include revascularization, percutaneous transluminal coronaryangioplasty (PTCA), and coronary artery bypass graft (CABG). Anginapectoris includes unstable angina in particular.

The SNPs described herein may further be useful for such cardiovascularevents as vulnerable plaque and stroke.

Myocardial Infarction (MI)

Myocardial infarction (MI), also referred to as a “heart attack”, is themost common cause of mortality in developed countries. The incidence ofMI is still high despite currently available preventive measures andtherapeutic intervention. More than 1,500,000 people in the U.S. sufferacute MI each year, many without seeking help due to unrecognized MI,and one third of these people die. The lifetime risk of coronary arterydisease events at age 40 is 42.4% for men, nearly one in two, and 24.9%for women, or one in four. D. M. Lloyd-Jones, Lancet 353:89-92 (1999).

MI is a multifactorial disease that involves atherogenesis, thrombusformation and propagation. Thrombosis can result in complete or partialocclusion of coronary arteries. The luminal narrowing or blockage ofcoronary arteries reduces oxygen and nutrient supply to the cardiacmuscle (cardiac ischemia), leading to myocardial necrosis and/orstunning. MI, unstable angina, and sudden ischemic death are clinicalmanifestations of cardiac muscle damage. All three endpoints are part ofacute coronary syndrome since the underlying mechanisms of acutecomplications of atherosclerosis are considered to be the same.

Atherogenesis, the first step of pathogenesis of MI, is a complexinteraction between blood elements, mechanical forces, disturbed bloodflow, and vessel wall abnormality that results in plaque accumulation.An unstable (vulnerable) plaque was recognized as an underlying cause ofarterial thrombotic events and MI. A vulnerable plaque is a plaque,often not stenotic, that has a high likelihood of becoming disrupted oreroded, thus forming a thrombogenic focus. MI due to a vulnerable plaqueis a complex phenomenon that includes: plaque vulnerability, bloodvulnerability (hypercoagulation, hypothrombolysis), and heartvulnerability (sensitivity of the heart to ischemia or propensity forarrhythmia). Recurrent myocardial infarction (RMI) can generally beviewed as a severe form of MI progression caused by multiple vulnerableplaques that are able to undergo pre-rupture or a pre-erosive state,coupled with extreme blood coagulability.

The current diagnosis of MI is based on the levels of troponin I or Tthat indicate the cardiac muscle progressive necrosis, impairedelectrocardiogram (ECG), and detection of abnormal ventricular wallmotion or angiographic data (the presence of acute thrombi). However,due to the asymptomatic nature of 25% of acute MIs (absence of atypicalchest pain, low ECG sensitivity), a significant portion of MIs are notdiagnosed and therefore not treated appropriately (e.g., prevention ofrecurrent MIs).

MI risk assessment and prognosis is currently done using classic riskfactors or the recently introduced Framingham Risk Index. Both of theseassessments put a significant weight on LDL levels to justify preventivetreatment. However, it is well established that half of all MIs occur inindividuals without overt hyperlipidemia.

Other emerging risk factors of MI are inflammatory biomarkers such asC-reactive protein (CRP), ICAM-1, SAA, TNF α, homocysteine, impairedfasting glucose, new lipid markers (ox LDL, Lp-a, MAD-LDL, etc.) andpro-thrombotic factors (fibrinogen, PAI-1). These markers havesignificant limitations such as low specificity and low positivepredictive value, and the need for multiple reference intervals to beused for different groups of people (e.g., males-females, smokers-nonsmokers, hormone replacement therapy users, different age groups). Theselimitations diminish the utility of such markers as independentprognostic markers for MI screening.

Genetics plays an important role in MI risk. Families with a positivefamily history of MI account for 14% of the general population, 72% ofpremature MIs, and 48% of all MIs. R. R. Williams, Am J Cardiology87:129 (2001). In addition, replicated linkage studies have revealedevidence of multiple regions of the genome that are associated with MIand relevant to MI genetic traits, including regions on chromosomes 14,2, 3 and 7, implying that genetic risk factors influence the onset,manifestation, and progression of MI. U. Broeckel, Nature Genetics30:210 (2002); S. Harrap, Arterioscler Thromb Vasc Biol 22:874-878(2002); A. Shearman, Human Molecular Genetics 9:1315-1320 (2000). Recentassociation studies have identified allelic variants that are associatedwith acute complications of CHD, including allelic variants of the ApoE,ApoA5, Lpa, APOCIII, and Klotho genes.

Genetic markers such as single nucleotide polymorphisms (SNPs) arepreferable to other types of biomarkers. Genetic markers that areprognostic for MI can be genotyped early in life and could predictindividual response to various risk factors. The combination of serumprotein levels and genetic predisposition revealed by genetic analysisof susceptibility genes can provide an integrated assessment of theinteraction between genotypes and environmental factors, resulting insynergistically increased prognostic value of diagnostic tests.

Thus, there is an urgent need for novel genetic markers that arepredictive of predisposition to CHD such as MI, particularly forindividuals who are unrecognized as having a predisposition to MI. Suchgenetic markers may enable prognosis of MI in much larger populationscompared with the populations that can currently be evaluated by usingexisting risk factors and biomarkers. The availability of a genetic testmay allow, for example, appropriate preventive treatments for acutecoronary events to be provided for susceptible individuals (suchpreventive treatments may include, for example, statin treatments andstatin dose escalation, as well as changes to modifiable risk factors),lowering of the thresholds for ECG and angiography testing, and allowadequate monitoring of informative biomarkers. Moreover, the discoveryof genetic markers associated with MI will provide novel targets fortherapeutic intervention or preventive treatments of MI, and enable thedevelopment of new therapeutic agents for treating or preventing MI andother cardiovascular disorders.

Furthermore, novel genetic markers that are predictive of predispositionto MI can be particularly useful for identifying individuals who are atrisk for early-onset MI. “Early-onset MI” may be defined as MI in menwho are less than 55 years of age and women who are less than 65 yearsof age. K. O. Akosah et al., “Preventing myocardial infarction in theyoung adult in the first place: How do the National CholesterolEducation Panel III guidelines perform?” JACC 41(9):1475-1479 (2003).Individuals who experience early-onset MI may not be effectivelyidentified by current cholesterol treatment guidelines, such as thosesuggested by the National Cholesterol Education Program. In one study,for example, a significant number of individuals who suffered MI at anearlier age (≤50 years) were shown to have LDL cholesterol below 100mg/dl. K. O. Akosah et al., “Myocardial infarction in young adults withlow-density lipoprotein cholesterol levels less than or equal to 100mg/dl. Clinical profile and 1-year outcomes.” Chest 120:1953-1958(2001). Because risk for MI can be reduced by lifestyle changes and bytreatment of modifiable risk factors, better methods to identifyindividuals at risk for early-onset MI could be useful for makingpreventive treatment decisions, especially considering that thesepatients may not be identified for medical management by conventionaltreatment guidelines. Genetic markers for risk of early-onset MI couldpotentially be incorporated into individual risk assessment protocols,as they have the advantage of being easily detected at any age.

Aortic Aneurysm and Dissection

Aortic aneurysm is the 13^(th) most common cause of death in the UnitedStates (Majumber et al., Am J Hum Genet 48(1):164-170,1991). Aorticaneurysm is a silent killer since, in the majority of cases, thecatastrophic sequelae is the first manifestation of the disease. Only10-15% of individuals survive an aneurysm rupture. Of those, only abouthalf survive emergency surgical repair (Powel et al., N Engl J Med 2003;348:1895-901).

Aortic aneurysm is a pathological dilation of the aorta, the largestvessel in the arterial system, which delivers oxygenated blood from theleft ventricle of the heart to the organs. When abnormal dilationundergoes progressive expansion, the aorta's media layers becomeincreasingly weakened due to micro apoplexy of the vessel wall, whichleads to higher wall stress, thereby inducing further progression ofdilation and aneurysm formation eventually resulting in aorticdissection, rupture and often death.

The clinical phenotype of aortic aneurysm may be divided into abdominalaortic aneurysms (AAA) and thoracic aortic aneurysms (TAA). Both TAA andAAA may be further subdivided into chronic aortic aneurysm (CAA) andaortic dissection (AD). Both AAA and TAA share risk factors such aschronic hypertension, smoking, older age, vascular inflammatorydiseases, deceleration trauma for aortic dissections, dyslipidemia, andthe main features of pathogenesis. Chronic hypertension, in particular,causes arterial wall intimal thickening, fibrosis, and calcificationcoupled with extracellular matrix degradation and elastolysis. Thisresults in intimal disruption at the edges of plaques (a process similarto coronary plaque rupture) and impairment of the oxygen supply to thearterial wall, followed by necrosis of smooth muscle cells and fibrosis.This process compromises elasticity of vessel walls and its resistanceto pulsatile forces—a morphologic basis for development of aneurysms anddissections (Nienaber et al., Circulation 2003 108:628-635).

Chronic aortic aneurysm (which may also be referred to asarteriosclerotic aneurysm) results from fusiform dilation. The abdominalaorta distal to the renal arteries is most commonly affected. When thethoracic aorta is involved, the aneurysm is usually in the descendingaorta. Organized thrombi are typically present inside the fusiformdilation. Although the aorta is markedly abnormal at the location of theaneurysm, the aorta is typically stretched concentrically, not dissectedlongitudinally, and the layers of the aortic wall are normally adherent.These aneurysms can rupture but they do not commonly dissect. Surgery iscarried out electively (if an aneurysm is detected) when these aneurysmsreach a size at which rupture becomes a significant danger (usually 6-8cm, or when the aneurysm begins to change rapidly).

Aortic dissection refers to a condition in which the layers of the aortaare split from each other, with blood under pressure entering betweentwo layers propagating the split and forming an additional false lumen.This process typically begins with a tear through the intima and innermedia at one specific site in the ascending or descending aorta.Dissections can harm an individual in several ways, including rupture ofthe aorta into the perecardium, chest or abdomen, cardiac tamponade, andaortic branch occlusion that can be followed by paraplegia, stroke, orrenal failure (Elefteriades et al, House Officer Guide to ICU Care,Reven Press, NY).

Aortic aneurysm has a strong genetic component. 18% of patients with AAAand 19% of patients with TAA were confirmed to have a first degreerelative affected with aortic aneurysm (Coady et al., Cardiol Clin. 1999November; 17(4):615-35; vii). For patients with a family history ofaortic aneurysm, the major risk factor is greater than 4 (Baird et al.,Lancet. 1995 Sep. 2; 346(8975):601-4) and it is twice as much for peoplewith coronary artery disease. In addition, familial studies haveidentified QTL of 5q13-14 in chromosome 5 (Guo et al., Circulation. 2001May 22; 103(20):2461-8) and QTL of 11q23.2-q24 in chromosome 11 (Vaughanet al., Circulation. 2001 May 22; 103(20):2469-75) associated withaneurysm formation.

The current diagnosis of aortic aneurysms is based on imagingtechnologies. However, imaging technologies have significantlimitations. For example, ultrasound is the procedure of choice fordiagnosing AAA. However, periodic screening for AAA by ultrasound is nota part of current guidelines for AAA diagnosis and treatment because itis not time and cost effective to screen individuals who do not haveclinical manifestation of disease. Consequently, due to the asymptomaticnature of the disease, a significant portion of aortic aneurysms are notdiagnosed until rupture or dissection occurs or, in rare instances,aneurysm is found accidentally during an unrelated ultrasound, CT, orMRI. The situation is even worse for TAA because diagnosis of TAA usingrelatively inexpensive ultrasound is not useful due to ultrasound's lackof sensitivity, and CT and MRI, although sensitive enough, are tooexpensive to justify for screening asymptomatic individuals.

The lack of reliable, inexpensive prognostic and diagnostic testsprevents health practitioners from appropriate monitoring of aneurysmsand using treatments of choice, such as beta blockers to slow downprogression of the disease or elective surgical intervention. Mortalityamong aortic aneurysm patients with non-ruptured aortic aneurysmstreated by elective surgery is 3-5% compared with 50-60% mortalityduring emergency surgery of ruptured aneurysms or dissections.

Thus, there is an urgent need for genetic markers that are predictive ofpredisposition to aortic aneurysm or dissection. Such genetic markerscould, for example, enable prognosis, diagnosis, and monitoring of AAAand TAA in much larger populations compared with the populations thatcan currently be evaluated using existing risk factors. Furthermore, theavailability of a genetic test could also enable preventive measures tobe initiated in susceptible individuals prior to the onset ofcatastrophic events. Such preventative measures may include, forexample, aggressive treatment of hypertension, use of beta-blockersand/or statin therapy, elective surgical intervention, and adequatemonitoring via imaging technologies and/or informative biomarkers.

Statin Treatment

Reduction of coronary and cerebrovascular events and total mortality bytreatment with HMG-CoA reductase inhibitors (statins) has beendemonstrated in a number of randomized, double-blinded,placebo-controlled prospective trials. D. D. Waters, Clin Cardiol 24(8Suppl):III3-7 (2001); B. K. Singh and J. L. Mehta, Curr Opin Cardiol17(5):503-11 (2002). These drugs have their primary effect through theinhibition of hepatic cholesterol synthesis, thereby upregulating LDLreceptors in the liver. The resultant increase in LDL catabolism resultsin decreased circulating LDL, a major risk factor for cardiovasculardisease.

Statins can be divided into two types according to their physicochemicaland pharmacokinetic properties. Statins such as lovastatin, simvastatin,atorvastatin, and cerevastatin are lipophilic in nature and, as such,diffuse across membranes and thus are highly cell permeable. Hydrophilicstatins such as pravastatin are more polar, such that they requirespecific cell surface transporters for cellular uptake. K. Ziegler andW. Stunkel, Biochim Biophys Acta 1139(3):203-9 (1992); M. Yamazaki etal., Am J Physiol 264(1 Pt 1):G36-44 (1993); T. Komai et al., BiochemPharmacol 43(4):667-70 (1992). The latter statin utilizes a transporter,OATP2, whose tissue distribution is confined to the liver and,therefore, they are relatively hepato-specific inhibitors. B. Hsiang etal., J Biol Chem 274(52):37161-37168 (1999). The former statins, notrequiring specific transport mechanisms, are available to all cells andthey can directly impact a much broader spectrum of cells and tissues.These differences in properties may influence the spectrum of activitiesthat each statin possesses. Pravastatin, for instance, has a lowmyopathic potential in animal models and myocyte cultures compared tolipophilic statins. B. A. Masters et al., Toxicol Appl Pharmacol 131(1):163-174 (1995); K. Nakahara et al., Toxicol Appl Pharmacol 152(1):99-106(1998); J. C. Reijneveld et al., Pediatr Res 39(6): 1028-1035 (1996).

Evidence from gene association studies is accumulating to indicate thatresponses to drugs are, indeed, at least partly under genetic control.As such, pharmacogenetics—the study of variability in drug responsesattributed to hereditary factors in different populations—maysignificantly assist in providing answers toward meeting this challenge.A. D. Roses, Nature 405(6788):857-865 (2000); V. Mooser et al., J ThrombHaemost 1(7):1398-1402 (2003); L. M. Humma and S. G. Terra, Am J HealthSyst Pharm 59(13):1241-1252 (2002). Numerous associations have beenreported between selected genotypes, as defined by SNPs and othergenetic sequence variations, and specific responses to cardiovasculardrugs. Polymorphisms in several genes have been suggested to influenceresponses to statins including CETP (J. A. Kuivenhoven et al., N Engl JMed 338(2):86-93 (1998)), beta-fibrinogen (M. P. de Maat et al.,Arterioscler Thromb Vasc Biol 18(2):265-71 (1998)), hepatic lipase (A.Zambon et al., Circulation 103(6):792-798 (2001)), lipoprotein lipase(J. W. Jukema et al., Circulation 94(8):1913-1918 (1996)), glycoproteinIIIa (P. F. Bray et al., Am J Cardiol 88(4):347-352 (2001)),stromelysin-1 (M. P. de Maat et al., Am J Cardiol 83(6):852-856 (1999)),and apolipoprotein E (L. U. Gerdes et al., Circulation 101(12):1366-1371(2000); J. Pedro-Botet et al., Atherosclerosis 158(1):183-193 (2001)).Some of these variants were shown to effect clinical events while otherswere associated with changes in surrogate endpoints.

Thus, there is a need for genetic markers that can be used to predict anindividual's responsiveness to statins. For example, there is a growingneed to better identify people who have the highest chance of benefitingfrom statins, and those who have the lowest risk of developingside-effects. For example, severe myopathies represent a significantrisk for a low percentage of the patient population, and this may be aparticular concern for patients who are treated more aggressively withstatins.

Single Nucleotide Polymorphisms (SNPs)

The genomes of all organisms undergo spontaneous mutation in the courseof their continuing evolution, generating variant forms of progenitorgenetic sequences. Gusella, Ann Rev Biochem 55:831-854 (1986). A variantform may confer an evolutionary advantage or disadvantage relative to aprogenitor form or may be neutral. In some instances, a variant formconfers an evolutionary advantage to the species and is eventuallyincorporated into the DNA of many or most members of the species andeffectively becomes the progenitor form. Additionally, the effects of avariant form may be both beneficial and detrimental, depending on thecircumstances. For example, a heterozygous sickle cell mutation confersresistance to malaria, but a homozygous sickle cell mutation is usuallylethal. In many cases, both progenitor and variant forms survive andco-exist in a species population. The coexistence of multiple forms of agenetic sequence gives rise to genetic polymorphisms, including SNPs.

Approximately 90% of all genetic polymorphisms in the human genome areSNPs. SNPs are single base positions in DNA at which different alleles,or alternative nucleotides, exist in a population. The SNP position(interchangeably referred to herein as SNP, SNP site, SNP locus, SNPmarker, or marker) is usually preceded by and followed by highlyconserved sequences of the allele (e.g., sequences that vary in lessthan 1/100 or 1/1000 members of the populations). An individual may behomozygous or heterozygous for an allele at each SNP position. A SNPcan, in some instances, be referred to as a “cSNP” to denote that thenucleotide sequence containing the SNP is an amino acid coding sequence.

A SNP may arise from a substitution of one nucleotide for another at thepolymorphic site. Substitutions can be transitions or transversions. Atransition is the replacement of one purine nucleotide by another purinenucleotide, or one pyrimidine by another pyrimidine. A transversion isthe replacement of a purine by a pyrimidine, or vice versa. A SNP mayalso be a single base insertion or deletion variant referred to as an“indel.” Weber et al., “Human diallelic insertion/deletionpolymorphisms,” Am J Hum Genet 71(4):854-62 (October 2002).

A synonymous codon change, or silent mutation/SNP (terms such as “SNP,”“polymorphism,” “mutation,” “mutant,” “variation,” and “variant” areused herein interchangeably), is one that does not result in a change ofamino acid due to the degeneracy of the genetic code. A substitutionthat changes a codon coding for one amino acid to a codon coding for adifferent amino acid (i.e., a non-synonymous codon change) is referredto as a missense mutation. A nonsense mutation results in a type ofnon-synonymous codon change in which a stop codon is formed, therebyleading to premature termination of a polypeptide chain and a truncatedprotein. A read-through mutation is another type of non-synonymous codonchange that causes the destruction of a stop codon, thereby resulting inan extended polypeptide product. While SNPs can be bi-, tri-, ortetra-allelic, the vast majority of the SNPs are bi-allelic, and arethus often referred to as “bi-allelic markers,” or “di-allelic markers.”

As used herein, references to SNPs and SNP genotypes include individualSNPs and/or haplotypes, which are groups of SNPs that are generallyinherited together. Haplotypes can have stronger correlations withdiseases or other phenotypic effects compared with individual SNPs, andtherefore may provide increased diagnostic accuracy in some cases.Stephens et al., Science 293:489-493 (July 2001).

Causative SNPs are those SNPs that produce alterations in geneexpression or in the expression, structure, and/or function of a geneproduct, and therefore are most predictive of a possible clinicalphenotype. One such class includes SNPs falling within regions of genesencoding a polypeptide product, i.e. cSNPs. These SNPs may result in analteration of the amino acid sequence of the polypeptide product (i.e.,non-synonymous codon changes) and give rise to the expression of adefective or other variant protein. Furthermore, in the case of nonsensemutations, a SNP may lead to premature termination of a polypeptideproduct. Such variant products can result in a pathological condition,e.g., genetic disease. Examples of genes in which a SNP within a codingsequence causes a genetic disease include sickle cell anemia and cysticfibrosis.

Causative SNPs do not necessarily have to occur in coding regions;causative SNPs can occur in, for example, any genetic region that canultimately affect the expression, structure, and/or activity of theprotein encoded by a nucleic acid. Such genetic regions include, forexample, those involved in transcription, such as SNPs in transcriptionfactor binding domains, SNPs in promoter regions, in areas involved intranscript processing, such as SNPs at intron-exon boundaries that maycause defective splicing, or SNPs in mRNA processing signal sequencessuch as polyadenylation signal regions. Some SNPs that are not causativeSNPs nevertheless are in close association with, and therefore segregatewith, a disease-causing sequence. In this situation, the presence of aSNP correlates with the presence of, or predisposition to, or anincreased risk in developing the disease. These SNPs, although notcausative, are nonetheless also useful for diagnostics, diseasepredisposition screening, and other uses.

An association study of a SNP and a specific disorder involvesdetermining the presence or frequency of the SNP allele in biologicalsamples from individuals with the disorder of interest, such as CHD, andcomparing the information to that of controls (i.e., individuals who donot have the disorder; controls may be also referred to as “healthy” or“normal” individuals) who are preferably of similar age and race. Theappropriate selection of patients and controls is important to thesuccess of SNP association studies. Therefore, a pool of individualswith well-characterized phenotypes is extremely desirable.

A SNP may be screened in diseased tissue samples or any biologicalsample obtained from a diseased individual, and compared to controlsamples, and selected for its increased (or decreased) occurrence in aspecific pathological condition, such as pathologies related to CHD andin particular, MI. Once a statistically significant association isestablished between one or more SNP(s) and a pathological condition (orother phenotype) of interest, then the region around the SNP canoptionally be thoroughly screened to identify the causative geneticlocus/sequence(s) (e.g., causative SNP/mutation, gene, regulatoryregion, etc.) that influences the pathological condition or phenotype.Association studies may be conducted within the general population andare not limited to studies performed on related individuals in affectedfamilies (linkage studies).

Clinical trials have shown that patient response to treatment withpharmaceuticals is often heterogeneous. There is a continuing need toimprove pharmaceutical agent design and therapy. In that regard, SNPscan be used to identify patients most suited to therapy with particularpharmaceutical agents (this is often termed “pharmacogenomics”).Similarly, SNPs can be used to exclude patients from certain treatmentdue to the patient's increased likelihood of developing toxic sideeffects or their likelihood of not responding to the treatment.Pharmacogenomics can also be used in pharmaceutical research to assistthe drug development and selection process. Linder et al., ClinicalChemistry 43:254 (1997); Marshall, Nature Biotechnology 15:1249 (1997);International Patent Application WO 97/40462, Spectra Biomedical; andSchafer et al., Nature Biotechnology 16:3 (1998).

SUMMARY OF THE INVENTION

The present invention relates to the identification of SNPs, as well asunique combinations of such SNPs and haplotypes of SNPs, that areassociated with CHD (particularly MI), aneurysm/dissection, and/or drugresponse, particularly response to statin treatment (includingpreventive treatment), such as for the treatment or prevention of CHD oraneurysm/dissection. The polymorphisms disclosed herein are directlyuseful as targets for the design of diagnostic and prognostic reagentsand the development of therapeutic and preventive agents for use in thediagnosis, prognosis, treatment, and/or prevention of CHD (particularlyMI) and aneurysm/dissection, as well as for predicting a patient'sresponse to therapeutic agents such as statins, particularly for thetreatment or prevention of CHD or aneurysm/dissection. Furthermore, thepolymorphisms disclosed herein are also useful for predicting anindividual's responsiveness to statins for the treatment or preventionof disorders other than CHD and aneurysm/dissection, such as cancer, andare also useful for predicting an individual's responsiveness to drugsother than statins that are used to treat or prevent CHD oraneurysm/dissection.

Certain exemplary embodiments of the invention relate in particular toSNP rs20455 and the association of this SNP with CHD (particularly MI),aneurysm/dissection, and drug response (particularly statin response),as well as SNPs that are in linkage disequilibrium with this SNP and/orare located in the genomic region surrounding this SNP. SNP rs20455 (thepublic rs identification number for this SNP), which is located in thekinesin-like protein 6 (KIF6) gene, is interchangeably referred toherein as “hCV3054799” (the internal identification number for thisSNP), the “KIF6 SNP”, the “Trp719Arg SNP”, the “Trp719Arg polymorphism”,“KIF6 Trp719Arg”, or just “Trp719Arg”. The risk allele for this SNP maybe interchangeably referred to herein as the “719Arg allele”, the “KIF6719Arg allele”, or just “719Arg” (further, an “allele” may beinterchangeably referred to herein as a “variant”). This is the allelethat is associated with increased risk for CHD and aneurysm/dissection,and which is also associated with greater benefit from statin treatment,as described herein and shown in the tables. As used herein, the term“benefit” (with respect to a drug) is defined as achieving a reducedrisk for a disease that the drug is intended to treat or prevent (e.g.,a CHD event such as MI) by administrating the drug treatment, comparedwith the risk for the disease in the absence of receiving the drugtreatment (or receiving a placebo in lieu of the drug treatment) for thesame genotype.

SNP rs20455, and its association with CHD (particularly MI) and statinresponse, is also described in the following references, each of whichis incorporated herein by reference in their entirety: Iakoubova et al.,“Association of the Trp719Arg polymorphism in kinesin-like protein 6with myocardial infarction and coronary heart disease in 2 prospectivetrials: the CARE and WOSCOPS trials”, J Am Coll Cardiol. 2008 Jan. 29;51(4):435-43, including Online Appendix (which relates in particular tothe association of SNP rs20455 with risk for CHD, including MI, andbenefit from statin treatment; the corresponding Online Appendix relatesto SNPs in linkage disequilibrium with rs20455); Shiffman et al., “Akinesin family member 6 variant is associated with coronary heartdisease in the Women's Health Study”, J Am Coll Cardiol. 2008 Jan. 29;51(4):444-8 (which relates in particular to the association of SNPrs20455 with risk for CHD, including MI, in women); Iakoubova et al.,“Polymorphism in KIF6 gene and benefit from statins after acute coronarysyndromes: results from the PROVE IT-TIMI 22 study”, J Am Coll Cardiol.2008 Jan. 29; 51(4):449-55 (which relates in particular to theassociation of SNP rs20455 with benefit from statin treatment, includingboth pravastatin and atorvastatin); and Shiffman et al., “Association ofgene variants with incident myocardial infarction in the CardiovascularHealth Study”, Arterioscler Thromb Vasc Biol. 2008 January; 28(1):173-9(which relates in particular to the association of SNP rs20455 with riskfor CHD, including MI, in elderly individuals ages 65 and older).

As shown and described herein, the KIF6 SNP (hCV3054799/rs20455) isassociated with risk for aortic aneurysm and aortic dissection, as wellas risk for other coronary events such as CHD (including MI). Therefore,this SNP has been shown to be associated with multiple differentcoronary events, and is therefore expected to have similar utilities inother coronary events. Consequently, the KIF6 SNP (hCV3054799/rs20455),as well as the other SNPs disclosed herein, is broadly useful withrespect to the full spectrum of coronary events. Furthermore, the KIF6SNP (hCV3054799/rs20455) has also been associated with othercardiovascular events such as stroke (see, e.g., U.S. provisional patentapplication 61/066,584, Luke et al., filed Feb. 20, 2008). Therefore,this SNP has been shown to be associated with multiple differentcardiovascular events, and is therefore expected to have similarutilities in other cardiovascular events. Consequently, the KIF6 SNP(hCV3054799/rs20455), as well as the other SNPs disclosed herein, isbroadly useful with respect to the full spectrum of cardiovascularevents. Moreover, this SNP has been specifically shown to be associatedwith benefit from statin treatment for reduction of MI, unstable angina,revascularization, and stroke events (see, e.g., Example 2). The KIF6SNP (hCV3054799/rs20455), as well as the other SNPs disclosed herein, isalso particularly useful for determining an individual's risk forvulnerable plaque.

Moreover, the exemplary utilities described herein for the KIF6 SNP(hCV3054799/rs20455), as well as the other SNPs disclosed herein, applyto both primary (i.e., first) and recurrent cardiovascular and coronaryevents. For example, the KIF6 SNP (hCV3054799/rs20455) can be used fordetermining the risk for a primary MI in an individual who has never hadan MI, and can also be used for determing the risk for a recurrent MI inan individual who has already had an MI.

Furthermore, the exemplary utilities described herein for the KIF6 SNP(hCV3054799/rs20455), as well as the other SNPs disclosed herein, applyto all individuals, including, but not limited to, both men and women(see Shiffman et al., “A kinesin family member 6 variant is associatedwith coronary heart disease in the Women's Health Study”, J Am CollCardiol. 2008 Jan. 29; 51(4):444-8 which relates to women inparticular), and all ages of individuals including elderly individuals(see Shiffman et al., “Association of gene variants with incidentmyocardial infarction in the Cardiovascular Health Study”, ArteriosclerThromb Vasc Biol. 2008 January; 28(1):173-9, which relates in particularto elderly individuals ages 65 and older, and the PROSPER studydescribed in Example 3 below, which relates in particular to elderlyindividuals ages 70-82) as well as younger individuals, etc.

Based on the identification of SNPs associated with CHD (particularlyMI), aneurysm/dissection, and/or response to statin treatment, thepresent invention also provides methods of detecting these variants aswell as the design and preparation of detection reagents needed toaccomplish this task. The invention specifically provides, for example,SNPs associated with CHD, aneurysm/dissection, and/or responsiveness tostatin treatment, isolated nucleic acid molecules (including DNA and RNAmolecules) containing these SNPs, variant proteins encoded by nucleicacid molecules containing such SNPs, antibodies to the encoded variantproteins, computer-based and data storage systems containing the novelSNP information, methods of detecting these SNPs in a test sample,methods of identifying individuals who have an altered (i.e., increasedor decreased) risk of developing CHD (particularly MI) andaneurysm/dissection, methods for determining the risk of an individualfor recurring CHD (e.g., recurrent MI) or recurring aneurysm/dissection,methods for prognosing the severity or consequences of CHD oraneurysm/dissection, methods of treating an individual who has anincreased risk for CHD or aneurysm/dissection, and methods foridentifying individuals (e.g., determining a particular individual'slikelihood) who have an altered (i.e., increased or decreased)likelihood of responding to statin treatment, particularly statintreatment of CHD (e.g., treatment or prevention of MI using statins) oraneurysm/dissection, based on the presence or absence of one or moreparticular nucleotides (alleles) at one or more SNP sites disclosedherein or the detection of one or more encoded variant products (e.g.,variant mRNA transcripts or variant proteins), methods of identifyingindividuals who are more or less likely to respond to a treatment (ormore or less likely to experience undesirable side effects from atreatment), methods of screening for compounds useful in the treatmentor prevention of a disorder associated with a variant gene/protein,compounds identified by these methods, methods of treating or preventingdisorders mediated by a variant gene/protein, methods of using the novelSNPs of the present invention for human identification, etc. The presentinvention also provides methods for identifying individuals who possessSNPs that are associated with an increased risk of developing CHD (suchas MI) or aneurysm/dissection, and yet can benefit from being treatedwith statin because statin treatment can lower their risk of developingCHD (such as MI) and statins may also be used in the prevention ortreatment of aneurysm/dissection.

The present invention further provides methods for selecting orformulating a treatment regimen (e.g., methods for determining whetheror not to administer statin treatment to an individual having CHD oraneurysm/dissection, or who is at risk for developing CHD oraneurysm/dissection in the future, or who has previously had CHD oraneurysm/dissection, methods for selecting a particular statin-basedtreatment regimen such as dosage and frequency of administration ofstatin, or a particular form/type of statin such as a particularpharmaceutical formulation or statin compound, methods for administeringan alternative, non-statin-based treatment to individuals who arepredicted to be unlikely to respond positively to statin treatment,etc.), and methods for determining the likelihood of experiencingtoxicity or other undesirable side effects from statin treatment, etc.The present invention also provides methods for selecting individuals towhom a statin or other therapeutic will be administered based on theindividual's genotype, and methods for selecting individuals for aclinical trial of a statin or other therapeutic agent based on thegenotypes of the individuals (e.g., selecting individuals to participatein the trial who are most likely to respond positively from the statintreatment and/or excluding individuals from the trial who are unlikelyto respond positively from the statin treament). The present inventionfurther provides methods for reducing an individual's risk of developingCHD (such as MI) or aneurysm/dissection using statin treatment,including preventing recurring CHD (e.g., recurrent MI) oraneurysm/dissection using statin treatment, when said individual carriesone or more SNPs identified herein as being associated with CHD.

In Tables 1 and 2, the present invention provides gene information,references to the identification of transcript sequences (SEQ ID NO: 1),encoded amino acid sequences (SEQ ID NO: 2), genomic sequences (SEQ IDNOS: 4-9), transcript-based context sequences (SEQ ID NO: 3) andgenomic-based context sequences (SEQ ID NOS: 10-132) that contain theSNPs of the present invention, and extensive SNP information thatincludes observed alleles, allele frequencies, populations/ethnic groupsin which alleles have been observed, information about the type of SNPand corresponding functional effect, and, for cSNPs, information aboutthe encoded polypeptide product. The actual transcript sequences (SEQ IDNO: 1), amino acid sequences (SEQ ID NO: 2), genomic sequences (SEQ IDNOS: 4-9), transcript-based SNP context sequences (SEQ ID NO: 3), andgenomic-based SNP context sequences (SEQ ID NOS: 10-132), together withprimer sequences (SEQ ID NOS: 133-189) are provided in the SequenceListing.

In certain exemplary embodiments, the invention provides a method foridentifying an individual who has an altered risk for developing a firstor recurrent CHD (e.g., MI) or aneurysm/dissection, in which the methodcomprises detecting a single nucleotide polymorphism (SNP) in any one ofthe nucleotide sequences of SEQ ID NO:1, SEQ ID NO:3, SEQ ID NOS:4-9,and SEQ ID NOS:10-132 in said individual's nucleic acids, wherein theSNP is specified in Table 1 and/or Table 2, and the presence of the SNPis indicative of an altered risk for CHD or aneurysm/dissection in saidindividual. In certain embodiments, the CHD is MI. In certain exemplaryembodiments of the invention, SNPs that occur naturally in the humangenome are provided as isolated nucleic acid molecules. These SNPs areassociated with CHD (particular MI), aneurysm/dissection, and/or drugresponse, particularly response to statin treatment, such that they canhave a variety of uses in the diagnosis, prognosis, treatment, and/orprevention of CHD, aneurysm/dissection, and related pathologies, andparticularly in the treatment or prevention of CHD oraneurysm/dissection using statins. In an alternative embodiment, anucleic acid of the invention is an amplified polynucleotide, which isproduced by amplification of a SNP-containing nucleic acid template. Inanother embodiment, the invention provides for a variant protein that isencoded by a nucleic acid molecule containing a SNP disclosed herein.

In yet another embodiment of the invention, a reagent for detecting aSNP in the context of its naturally-occurring flanking nucleotidesequences (which can be, e.g., either DNA or mRNA) is provided. Inparticular, such a reagent may be in the form of, for example, ahybridization probe or an amplification primer that is useful in thespecific detection of a SNP of interest. In an alternative embodiment, aprotein detection reagent is used to detect a variant protein that isencoded by a nucleic acid molecule containing a SNP disclosed herein. Apreferred embodiment of a protein detection reagent is an antibody or anantigen-reactive antibody fragment.

Various embodiments of the invention also provide kits comprising SNPdetection reagents, and methods for detecting the SNPs disclosed hereinby employing detection reagents. In a specific embodiment, the presentinvention provides for a method of identifying an individual having anincreased or decreased risk of developing CHD (e.g., having an MI) oraneurysm/dissection by detecting the presence or absence of one or moreSNP alleles disclosed herein. In another embodiment, a method fordiagnosis of CHD or aneurysm/dissection by detecting the presence orabsence of one or more SNP alleles disclosed herein is provided. Thepresent invention also provides methods for evaluating whether anindividual is likely (or unlikely) to respond to statin treatment,particularly statin treatment of CHD or aneurysm/dissection, bydetecting the presence or absence of one or more SNP alleles disclosedherein.

The nucleic acid molecules of the invention can be inserted in anexpression vector, such as to produce a variant protein in a host cell.Thus, the present invention also provides for a vector comprising aSNP-containing nucleic acid molecule, genetically-engineered host cellscontaining the vector, and methods for expressing a recombinant variantprotein using such host cells. In another specific embodiment, the hostcells, SNP-containing nucleic acid molecules, and/or variant proteinscan be used as targets in a method for screening and identifyingtherapeutic agents or pharmaceutical compounds useful in the treatmentor prevention of CHD (particularly MI) or aneurysm/dissection.

An aspect of this invention is a method for treating or preventing afirst or recurrent CHD (e.g., MI) or aneurysm/dissection, in a humansubject wherein said human subject harbors a SNP, gene, transcript,and/or encoded protein identified in Tables 1 and 2, which methodcomprises administering to said human subject a therapeutically orprophylactically effective amount of one or more agents (e.g., statins,including but not limited to, storvastatin, pravastatin, atorvastatin,etc.) counteracting the effects of the disease, such as by inhibiting(or stimulating) the activity of a gene, transcript, and/or encodedprotein identified in Tables 1 and 2.

Another aspect of this invention is a method for identifying an agentuseful in therapeutically or prophylactically treating CHD (particularlyMI) or aneurysm/dissection, in a human subject wherein said humansubject harbors a SNP, gene, transcript, and/or encoded proteinidentified in Tables 1 and 2, which method comprises contacting thegene, transcript, or encoded protein with a candidate agent (e.g., astatin, including but not limited to, storvastatin, pravastatin,atorvastatin, etc.) under conditions suitable to allow formation of abinding complex between the gene, transcript, or encoded protein and thecandidate agent and detecting the formation of the binding complex,wherein the presence of the complex identifies said agent.

Another aspect of this invention is a method for treating or preventingCHD (such as MI) or aneurysm/dissection, in a human subject, in whichthe method comprises:

(i) determining that said human subject harbors a SNP, gene, transcript,and/or encoded protein identified in Tables 1 and 2, and

(ii) administering to said subject a therapeutically or prophylacticallyeffective amount of one or more agents (such as a statin, including butnot limited to, storvastatin, pravastatin, atorvastatin, etc.)counteracting the effects of the disease such as statins.

Another aspect of the invention is a method for identifying a human whois likely to benefit from statin treatment, in which the methodcomprises detecting the presence of the risk allele of SNP rs20455 insaid human's nucleic acids, wherein the presence of the risk alleleindicates that said human is likely to benefit from statin treatment.

Another aspect of the invention is a method for identifying a human whois likely to benefit from statin treatment, in which the methodcomprises detecting the presence of the risk allele of a SNP that is inLD with SNP rs20455 in said human's nucleic acids, wherein the presenceof the risk allele of the LD SNP indicates that said human is likely tobenefit from statin treatment.

Exemplary embodiments of the invention include methods of using SNPrs20455 related to any statin. It has been specifically shown hereinthat carriers of the KIF6 719Arg allele benefit from not onlypravastatin (Pravachol®), which is a hydrophilic statin, but alsoatorvastatin (Lipitor®), which is a lipophilic statin (as described inExample 2 below, in particular). This SNP is therefore expected to havesimilar utilities across the entire class of statins, particularly sinceit has specifically been shown to be useful for both hydrophilic andlipophilic statins. Thus, this SNP, as well as the other statinresponse-associated SNPs disclosed herein, is broadly useful inpredicting the therapeutic effect for the entire class of statins, suchas for determining whether an individual will benefit from any of thestatins, including, but not limited to, fluvastatin (Lescol®),lovastatin (Mevacor®), rosuvastatin (Crestor®), and simvastatin(Zocor®), as well as combination therapies that include a statin such assimvastatin+ezetimibe (Vytorin®), lovastatin+niacin extended-release(Advicor®), and atorvastatin+amlodipine besylate (Caduet®).

In certain exemplary embodiments of the invention, the diagnosticmethods are directed to the determination of which patients would havegreater protection against CHD (e.g., MI, recurrent MI, etc.) oraneurysm/dissection when they are given an intensive statin treatment ascompared to a standard statin treatment. In certain embodiments, thestatin can comprise a statin selected from the group consisting ofatorvastatin, pravastatin, and storvastatin. In certain embodiments,intensive statin treatment comprises administering higher doses of astatin and/or increasing the frequency of statin administration ascompared with standard statin treatment. In certain further embodiments,intensive statin treatment can utilize a different type of statin thanstandard statin treatment; for example, atorvastatin can be used forintensive statin treatment and pravastatin can be used for standardstatin treatment.

Many other uses and advantages of the present invention will be apparentto those skilled in the art upon review of the detailed description ofthe preferred embodiments herein. Solely for clarity of discussion, theinvention is described in the sections below by way of non-limitingexamples.

Description of the Files Contained on the CD-R Named CDR Duplicate Copy1 and CDR Duplicate Copy 2

Each of the CD-Rs contains the following text file: FileCD000014ORD_SEQLIST.txt provides the Sequence Listing. The SequenceListing provides the transcript sequences (SEQ ID NO: 1) and proteinsequences (SEQ ID NO: 2) as referred to in Table 1, and genomicsequences (SEQ ID NOS: 4-9) as referred to in Table 2, for each CHD,aneurysm/dissection, and/or drug response-associated gene (or genomicregion for intergenic SNPs) that contains one or more SNPs of thepresent invention. Also provided in the Sequence Listing are contextsequences flanking each SNP, including both transcript-based contextsequences as referred to in Table 1 (SEQ ID NO: 3) and genomic-basedcontext sequences as referred to in Table 2 (SEQ ID NOS: 10-132). Inaddition, the Sequence Listing provides the primer sequences from Table3 (SEQ ID NOS: 133-189), which are oligonucleotides that have beensynthesized and used in the laboratory to assay certain SNPs disclosedherein by allele-specific PCR during the course of association studiesto verify the association of these SNPs with CHD, aneurysm/dissection,and/or drug response. The context sequences generally provide 100 bpupstream (5′) and 100 bp downstream (3′) of each SNP, with the SNP inthe middle of the context sequence, for a total of 200 bp of contextsequence surrounding each SNP.

File CD000014ORD_SEQLIST.txt is 614 KB in size, and was created on Mar.20, 2008. A computer readable format of the sequence listing is alsosubmitted herein on a separate CDR labeled CRF. In accordance with 37C.F.R. § 1.821(f), the information recorded in the CRF CDR is identicalto the sequence listing as provided on the CDR Duplicate Copy 1 and Copy2.

The material contained on the CD-R is hereby incorporated by referencepursuant to 37 CFR 1.77(b)(4).

Description of Table 1 and Table 2

Table 1 and Table 2 (both provided on the CD-R) disclose the SNP andassociated gene/transcript/protein information of the present invention.For each gene, Table 1 provides a header containing gene, transcript andprotein information, followed by a transcript and protein sequenceidentifier (SEQ ID NO), and then SNP information regarding each SNPfound in that gene/transcript including the transcript context sequence.For each gene in Table 2, a header is provided that contains gene andgenomic information, followed by a genomic sequence identifier (SEQ IDNO) and then SNP information regarding each SNP found in that gene,including the genomic context sequence.

Note that SNP markers may be included in both Table 1 and Table 2; Table1 presents the SNPs relative to their transcript sequences and encodedprotein sequences, whereas Table 2 presents the SNPs relative to theirgenomic sequences. In some instances Table 2 may also include, after thelast gene sequence, genomic sequences of one or more intergenic regions,as well as SNP context sequences and other SNP information for any SNPsthat lie within these intergenic regions. Additionally, in either Table1 or 2 a “Related Interrogated SNP” may be listed following a SNP whichis determined to be in LD with that interrogated SNP according to thegiven Power value. SNPs can be readily cross-referenced between allTables based on their Celera hCV (or, in some instances, hDV)identification numbers and/or public rs identification numbers, and tothe Sequence Listing based on their corresponding SEQ ID NOs.

The gene/transcript/protein information includes:

-   -   a gene number (1 through n, where n=the total number of genes in        the Table),    -   a Celera hCG and UID internal identification numbers for the        gene,    -   a Celera hCT and UID internal identification numbers for the        transcript (Table 1 only),    -   a public Genbank accession number (e.g., RefSeq NM number) for        the transcript (Table 1 only),    -   a Celera hCP and UID internal identification numbers for the        protein encoded by the hCT transcript (Table 1 only),    -   a public Genbank accession number (e.g., RefSeq NP number) for        the protein (Table 1 only),    -   an art-known gene symbol,    -   an art-known gene/protein name,    -   Celera genomic axis position (indicating start nucleotide        position-stop nucleotide position),    -   the chromosome number of the chromosome on which the gene is        located,    -   an OMIM (Online Mendelian Inheritance in Man; Johns Hopkins        University/NCBI) public reference number for obtaining further        information regarding the medical significance of each gene, and    -   alternative gene/protein name(s) and/or symbol(s) in the OMIM        entry.

Note that, due to the presence of alternative splice forms, multipletranscript/protein entries may be provided for a single gene entry inTable 1; i.e., for a single Gene Number, multiple entries may beprovided in series that differ in their transcript/protein informationand sequences.

Following the gene/transcript/protein information is a transcriptcontext sequence (Table 1), or a genomic context sequence (Table 2), foreach SNP within that gene.

After the last gene sequence, Table 2 may include additional genomicsequences of intergenic regions (in such instances, these sequences areidentified as “Intergenic region:” followed by a numericalidentification number), as well as SNP context sequences and other SNPinformation for any SNPs that lie within each intergenic region (suchSNPs are identified as “INTERGENIC” for SNP type).

Note that the transcript, protein, and transcript-based SNP contextsequences are all provided in the Sequence Listing. The transcript-basedSNP context sequences are provided in both Table 1 and also in theSequence Listing. The genomic and genomic-based SNP context sequencesare provided in the Sequence Listing. The genomic-based SNP contextsequences are provided in both Table 2 and in the Sequence Listing. SEQID NOs are indicated in Table 1 for the transcript-based contextsequences (SEQ ID NO: 3); SEQ ID NOs are indicated in Table 2 for thegenomic-based context sequences (SEQ ID NOS: 10-132).

The SNP information includes:

-   -   Context sequence (taken from the transcript sequence in Table 1,        the genomic sequence in Table 2) with the SNP represented by its        IUB code, including 100 bp upstream (5′) of the SNP position        plus 100 bp downstream (3′) of the SNP position (the        transcript-based SNP context sequences in Table 1 are provided        in the Sequence Listing as SEQ ID NO: 3; the genomic-based SNP        context sequences in Table 2 are provided in the Sequence        Listing as SEQ ID NOS: 10-132).    -   Celera hCV internal identification number for the SNP (in some        instances, an “hDV” number is given instead of an “hCV” number).    -   The corresponding public identification number for the SNP, the        rs number.    -   SNP position (position of the SNP within the given transcript        sequence (Table 1) or within the given genomic sequence (Table        2)).    -   “Related Interrogated SNP” as the interrogated SNP with which        the listed SNP is in LD at the given value of Power.    -   SNP source (may include any combination of one or more of the        following five codes, depending on which internal sequencing        projects and/or public databases the SNP has been observed in:        “Applera”=SNP observed during the re-sequencing of genes and        regulatory regions of 39 individuals, “Celera”=SNP observed        during shotgun sequencing and assembly of the Celera human        genome sequence, “Celera Diagnostics”=SNP observed during        re-sequencing of nucleic acid samples from individuals who have        a disease, “dbSNP”=SNP observed in the dbSNP public database,        “HGBASE”=SNP observed in the HGBASE public database, “HGMD”=SNP        observed in the Human Gene Mutation Database (HGMD) public        database, “HapMap”=SNP observed in the International HapMap        Project public database, “CSNP”=SNP observed in an internal        Applied Biosystems (Foster City, Calif.) database of coding SNPS        (cSNPs).

Note that multiple “Applera” source entries for a single SNP indicatethat the same SNP was covered by multiple overlapping amplificationproducts and the re-sequencing results (e.g., observed allele counts)from each of these amplification products is being provided.

-   -   Population/allele/allele count information in the format of        [population1(first_allele,count|second_allele,count)population2(first_allele,count|second_allele,coun t)        total (first_allele,total count|second_allele,total count)]. The        information in this field includes populations/ethnic groups in        which particular SNP alleles have been observed        (“cau”=Caucasian, “his”=Hispanic, “chn”=Chinese, and        “afr”=African-American, “jpn”=Japanese, “ind”=Indian,        “mex”=Mexican, “ain”=“American Indian, “cra”=Celera donor,        “no_pop”=no population information available), identified SNP        alleles, and observed allele counts (within each population        group and total allele counts), where available [“−” in the        allele field represents a deletion allele of an        insertion/deletion (“indel”) polymorphism (in which case the        corresponding insertion allele, which may be comprised of one or        more nucleotides, is indicated in the allele field on the        opposite side of the “|”); “-” in the count field indicates that        allele count information is not available]. For certain SNPs        from the public dbSNP database, population/ethnic information is        indicated as follows (this population information is publicly        available in dbSNP): “HISP1”=human individual DNA (anonymized        samples) from 23 individuals of self-described HISPANIC        heritage; “PACI”=human individual DNA (anonymized samples) from        24 individuals of self-described PACIFIC RIM heritage;        “CAUC1”=human individual DNA (anonymized samples) from 31        individuals of self-described CAUCASIAN heritage; “AFR1”=human        individual DNA (anonymized samples) from 24 individuals of        self-described AFRICAN/AFRICAN AMERICAN heritage; “P1”=human        individual DNA (anonymized samples) from 102 individuals of        self-described heritage; “PA130299515”; “SC_12_A”=SANGER 12 DNAs        of Asian origin from Corielle cell repositories, 6 of which are        male and 6 female; “SC_12_C”=SANGER 12 DNAs of Caucasian origin        from Corielle cell repositories from the CEPH/UTAH library, six        male and six female; “SC_12 AA”=SANGER 12 DNAs of        African-American origin from Corielle cell repositories 6 of        which are male and 6 female; “SC_95_C”=SANGER 95 DNAs of        Caucasian origin from Corielle cell repositories from the        CEPH/UTAH library; and “SC_12_CA”=Caucasians—12 DNAs from        Corielle cell repositories that are from the CEPH/UTAH library,        six male and six female.

Note that for SNPs of “Applera” SNP source, genes/regulatory regions of39 individuals (20 Caucasians and 19 African Americans) werere-sequenced and, since each SNP position is represented by twochromosomes in each individual (with the exception of SNPs on X and Ychromosomes in males, for which each SNP position is represented by asingle chromosome), up to 78 chromosomes were genotyped for each SNPposition. Thus, the sum of the African-American (“afr”) allele counts isup to 38, the sum of the Caucasian allele counts (“cau”) is up to 40,and the total sum of all allele counts is up to 78.

Note that semicolons separate population/allele/count informationcorresponding to each indicated SNP source; i.e., if four SNP sourcesare indicated, such as “Celera,” “dbSNP,” “HGBASE,” and “HGMD,” thenpopulation/allele/count information is provided in four groups which areseparated by semicolons and listed in the same order as the listing ofSNP sources, with each population/allele/count information groupcorresponding to the respective SNP source based on order; thus, in thisexample, the first population/allele/count information group wouldcorrespond to the first listed SNP source (Celera) and the thirdpopulation/allele/count information group separated by semicolons wouldcorrespond to the third listed SNP source (HGBASE); ifpopulation/allele/count information is not available for any particularSNP source, then a pair of semicolons is still inserted as aplace-holder in order to maintain correspondence between the list of SNPsources and the corresponding listing of population/allele/countinformation.

-   -   SNP type (e.g., location within gene/transcript and/or predicted        functional effect) [“MISSENSE MUTATION”=SNP causes a change in        the encoded amino acid (i.e., a non-synonymous coding SNP);        “SILENT MUTATION”=SNP does not cause a change in the encoded        amino acid (i.e., a synonymous coding SNP); “STOP CODON        MUTATION”=SNP is located in a stop codon; “NONSENSE        MUTATION”=SNP creates or destroys a stop codon; “UTR 5”=SNP is        located in a 5′ UTR of a transcript; “UTR 3”=SNP is located in a        3′ UTR of a transcript; “PUTATIVE UTR 5”=SNP is located in a        putative 5′ UTR; “PUTATIVE UTR 3”=SNP is located in a putative        3′ UTR; “DONOR SPLICE SITE”=SNP is located in a donor splice        site (5′ intron boundary); “ACCEPTOR SPLICE SITE”=SNP is located        in an acceptor splice site (3′ intron boundary); “CODING        REGION”=SNP is located in a protein-coding region of the        transcript; “EXON”=SNP is located in an exon; “INTRON”=SNP is        located in an intron; “hmCS”=SNP is located in a human-mouse        conserved segment; “TFBS”=SNP is located in a transcription        factor binding site; “UNKNOWN”=SNP type is not defined;        “INTERGENIC”=SNP is intergenic, i.e., outside of any gene        boundary].    -   Protein coding information (Table 1 only), where relevant, in        the format of [protein SEQ ID NO, amino acid position, (amino        acid-1, codon1) (amino acid-2, codon2)]. The information in this        field includes SEQ ID NO of the encoded protein sequence,        position of the amino acid residue within the protein identified        by the SEQ ID NO that is encoded by the codon containing the        SNP, amino acids (represented by one-letter amino acid codes)        that are encoded by the alternative SNP alleles (in the case of        stop codons, “X” is used for the one-letter amino acid code),        and alternative codons containing the alternative SNP        nucleotides which encode the amino acid residues (thus, for        example, for missense mutation-type SNPs, at least two different        amino acids and at least two different codons are generally        indicated; for silent mutation-type SNPs, one amino acid and at        least two different codons are generally indicated, etc.). In        instances where the SNP is located outside of a protein-coding        region (e.g., in a UTR region), “None” is indicated following        the protein SEQ ID NO.

Description of Table 3

Table 3 provides sequences (SEQ ID NOS:133-189) of primers that havebeen synthesized and used in the laboratory to assay certain SNPsdisclosed herein by allele-specific PCR during the course of associationstudies to verify the association of these SNPs with CHD,aneurysm/dissection, and/or statin response (see Examples section).

Table 3 provides the following:

-   -   the column labeled “Marker” provides an hCV identification        number for each SNP that can be detected using the corresponding        primers.    -   the column labeled “Alleles” designates the two alternative        alleles (i.e., nucleotides) at the SNP site. These alleles are        targeted by the allele-specific primers (the allele-specific        primers are shown as Primer 1 and Primer 2). Note that alleles        may be presented in Table 3 based on a different orientation        (i.e., the reverse complement) relative to how the same alleles        are presented in Tables 1-2.    -   the column labeled “Primer 1 (Allele-Specific Primer)” provides        an allele-specific primer that is specific for an allele        designated in the “Alleles” column.    -   the column labeled “Primer 2 (Allele-Specific Primer)” provides        an allele-specific primer that is specific for the other allele        designated in the “Alleles” column.    -   the column labeled “Common Primer” provides a common primer that        is used in conjunction with each of the allele-specific primers        (i.e., Primer 1 and Primer 2) and which hybridizes at a site        away from the SNP position.

All primer sequences are given in the 5′ to 3′ direction.

Each of the nucleotides designated in the “Alleles” column matches or isthe reverse complement of (depending on the orientation of the primerrelative to the designated allele) the 3′ nucleotide of theallele-specific primer (i.e., either Primer 1 or Primer 2) that isspecific for that allele.

Description of Table 4

Table 4 provides a list of LD SNPs that are related to and derived fromcertain interrogated SNPs. The interrogated SNPs, which are shown incolumn 1 (which indicates the hCV identification numbers of eachinterrogated SNP) and column 2 (which indicates the public rsidentification numbers of each interrogated SNP) of Table 4, arestatistically significantly associated with CHD, aneurysm/dissection,and/or statin response, as described and shown herein, particularly inTables 5-22 and in the Examples section below. The LD SNPs are providedas an example of SNPs which can also serve as markers for diseaseassociation based on their being in LD with an interrogated SNP. Thecriteria and process of selecting such LD SNPs, including thecalculation of the r² value and the r² threshold value, are described inExample 6, below.

In Table 4, the column labeled “Interrogated SNP” presents each markeras identified by its unique hCV identification number. The columnlabeled “Interrogated rs” presents the publicly known rs identificationnumber for the corresponding hCV number. The column labeled “LD SNP”presents the hCV numbers of the LD SNPs that are derived from theircorresponding interrogated SNPs. The column labeled “LD SNP rs” presentsthe publicly known rs identification number for the corresponding hCVnumber. The column labeled “Power” presents the level of power where ther² threshold is set. For example, when power is set at 0.51, thethreshold r² value calculated therefrom is the minimum r² that an LD SNPmust have in reference to an interrogated SNP, in order for the LD SNPto be classified as a marker capable of being associated with a diseasephenotype at greater than 51% probability. The column labeled “Thresholdr²” presents the minimum value of r² that an LD SNP must meet inreference to an interrogated SNP in order to qualify as an LD SNP. Thecolumn labeled “r²” presents the actual r² value of the LD SNP inreference to the interrogated SNP to which it is related.

Description of Tables 5-22

Tables 5-22 provide the results of statistical analyses for SNPsdisclosed in Tables 1 and 2 (SNPs can be cross-referenced between allthe tables herein based on their hCV and/or rs identification numbers).The results shown in Tables 5-22 provide support for the association ofthese SNPs with CHD, particularly MI and recurrent MI (RMI),aneurysm/dissection, and/or the association of these SNPs with drugresponse, such as statins administered as a preventive treatment forMI/RMI. As an example, the statistical results provided in Tables 5-7show that the association of SNP hCV3054799 in the kinesin-like protein6 (KIF6) gene (this SNP is also interchangeably referred to herein asKIF6 Trp719Arg or rs20455, its public rs identification number) withrisk of MI/RMI, as well as with response to statin treatment in theprevention of MI/RMI, is supported by p-values <0.05 in genotypicassociation tests.

Tables 5-7 show the association of SNP hCV3054799 with CHD risk and drugresponse (p<0.05 in either a genotypic or dominant test) in CARE andWOSCOPS samples. Tables 5-7 specifically provide analysis showing theassociation of hCV3054799 with MI/CHD risks and the association of thisSNP with prevention of MI/CHD by statin treatment. Table 5 shows theassociation of KIF6 Trp719Arg (hCV3054799) with MI and CHD in theplacebo arms of the CARE and WOSCOPS trials. Table 6 shows the effect ofpravastatin on MI and CHD in KIF6 Trp719Arg (hCV3054799) subgroups fromthe CARE and WOSCOPS trials. Table 7 shows the effect on CHD ofatorvastatin compared with pravastatin according to KIF6 Trp719Arggenotype. See Example 1 for further information relating to Tables 5-6,and see Example 2 for further information relating to Table 7.

Tables 8-13 show the association of SNP hCV3054799 with CHD risk anddrug response (p<0.05 in either a genotypic or dominant test) in PROSPERsamples. Tables 8 and 9 show the association of the KIF6 SNP (rs20455)with risk of CHD in the placebo arm of the PROSPER trial (an elderlypopulation, ages 70-82). Table 8 shows the number of patients of thethree genotypes and carriers (minor homozygote+heterozygote) in theplacebo arm of the PROSPER trial. Table 9 shows that, for example, amongthose in the placebo group with prior vascular disease, 719Arg carriers(59.0%) were at nominally greater risk for coronary events compared withnoncarriers: hazard ratio=1.25 (95% CI 0.95 to 1.64). Tables 10-13 showthe effect of pravastatin compared with placebo on risk of CHD inpopulation subgroups of the PROSPER trial defined by KIF6 SNP (rs20455)genotypes. Table 10 shows the number of patients of the three genotypesand carriers (minor homozygote+heterozygote) in the placebo arm of thePROSPER trial. Table 11 shows the number of patients of the threegenotypes and carriers (minor homozygote+heterozygote) in thepravastatin arm of the PROSPER trial. To assess the effect ofpravastatin, risk estimates were used to compare the pravastatin armwith the placebo arm in subgroups defined by genotypes. Table 12 showsthat, for example, among 719Arg carriers with prior vascular disease, asubstantial and significant benefit from pravastatin therapy wasobserved (hazard ratio 0.67, 95% CI 0.52 to 0.87), whereas nosignificant benefit was observed in noncarriers (hazard ratio 0.92, 95%CI 0.68 to 1.25). Table 13 shows the interaction between 719Arg carrierstatus and pravastatin treatment (p=0.12). See Example 3 for furtherinformation relating to Tables 8-13.

Table 14 shows SNPs from the genomic region around SNP hCV3054799 thatare associated with CHD risk (p<0.15 in either a genotypic, additive,dominant, or recessive test) in CARE and WOSCOPS samples. Themeta-analysis results presented in Table 14 specifically show that sixSNPs (the KIF6 Trp719Arg SNP (rs20455), as well as rs9471077, rs9462535,rs9394584, rs11755763, and rs9471080) were associated with recurrent MIin the placebo arm of CARE and with CHD in the placebo arm of WOSCOPS(p<0.05 in meta-analysis), with KIF6 Trp719Arg and rs9471077 beingparticularly strongly associated. rs9471077 is in strong linkagedisequilibrium with the Trp719Arg SNP (r²=0.79 in placebo-treatedpatients), and the risk ratios for Trp719Arg and rs9471077 were similarin the placebo arms of CARE and WOSCOPS. After adjusting forconventional risk factors, the hazard ratios were 1.57 and 1.54 (p=0.01and 0.02) in CARE for Trp719Arg and rs9471077, respectively, and theadjusted odds ratios were 1.59 and 1.46 (p=0.003 and 0.01) in WOSCOPSfor Trp719Arg and rs9471077, respectively. See Example 4 for furtherinformation relating to Table 14.

Table 15 shows SNPs from a fine-mapping analysis of the genomic regionaround SNP hCV3054799 that are associated with CHD risk (p<0.1 in eithera genotypic, additive, dominant, or recessive test) in CARE samples.Table 15, which provides the association results for recurrent MI andthe counts for different genotypes in the placebo arm of CARE, showsthat certain genotypes in six SNPs were associated with recurrent MI.See “Example 4—Supplemental Analysis” section for further informationrelating to Table 15.

Table 16 shows SNPs from the genomic region around SNP hCV3054799 thatare associated with drug response (p<0.05 in either genotypes) in CAREsamples. Table 16 specifically shows SNPs having a significant (p-valueof less than 0.05) association with an effect of pravastatin treatment(compared with placebo) on risk of recurrent MI (RMI) in subgroups ofCARE defined by genotypes. See “Example 4—Supplemental Analysis” sectionfor further information relating to Table 16.

Tables 17-20 show that the KIF6 SNP (hCV3054799) is associated with riskfor aortic aneurysm and dissection (p<0.05 in either a genotypic,allelic, dominant, or recessive test). To determine whether the KIF6 SNP(hCV3054799) is associated with aortic aneurysm or dissection, this SNPwas analyzed using the following two endpoints: (1) using aorticaneurysm or aortic dissection as an endpoint, which compared patientswith aneurysm or dissection against patients without aneurysm ordissection (shown in Table 17), and (2) using aortic dissection as anendpoint, which compared patients with dissection against patientswithout dissection (shown in Table 18). Based on this analysis, the KIF6SNP (hCV3054799) was found to be associated (p-value ≤0.05) withaneurysm or dissection and with dissection only, and the risk allele inboth instances was the same allele that was previously associated withMI for this SNP (genotype counts for the aneurysm or dissection endpointare shown in Table 19, and genotype counts for the dissection endpointare shown in Table 20). See Example 5 for further information relatingto Tables 17-20. Table 21 shows that the KIF6 SNP (hCV3054799) isassociated with aneurysm/dissection among patients without CHD and,therefore, the association of the KIF6 SNP with aneurysm/dissection isindependent of CHD. See the “Example 5—Supplemental Analysis” sectionfor further information relating to Table 21.

Table 22 shows the results of an analysis of SNPs from Table 14 (otherthan the KIF6 Trp719Arg SNP, which is shown elsewhere herein to beassociated with drug response, particularly benefit from statintreatment) to determine whether individuals with increased risk of CHDwill benefit from pravastatin treatment. Table 22 shows that, besidesthe KIF6 Trp719Arg SNP, four other SNPs in Table 14(rs9471080/hCV29992177, rs9394584/hCV30225864, rs9471077/hCV3054813, andrs9462535/hCV3054808) are associated with benefit from pravastatintreatment in CARE and WOSCOPS samples, as well as being associated withCHD risk (as shown in Table 14).

Throughout Tables 5-22, “OR” refers to the odds ratio, “HR” or “HRR”refers to the hazard ratio, and “90% CI” or “95% CI” refers to the 90%or 95% confidence interval (respectively) for the odds ratio or hazardratio (the confidence intervals, as presented in the tables, may specifythe lower and upper bounds as a range, or may individually specify thelower bound and the upper bound). Odds ratios (OR) or hazard ratios (HRor HRR) that are greater than one indicate that a given allele (orcombination of alleles such as a haplotype, diplotype, or two-locusdiplotype) is a risk allele (which may also be referred to as asusceptibility allele), whereas odds ratios or hazard ratios that areless than one indicate that a given allele is a non-risk allele (whichmay also be referred to as a protective allele). For a given riskallele, the other alternative allele at the SNP position (which can bederived from the information provided in Tables 1-2, for example) may beconsidered a non-risk allele. For a given non-risk allele, the otheralternative allele at the SNP position may be considered a risk allele.

Thus, with respect to disease risk (e.g., CHD such as MI, oraneurysm/dissection), if the risk estimate (odds ratio or hazard ratio)for a particular genotype is greater than one, this indicates that anindividual with this particular genotype has a higher risk for thedisease than an individual who has the reference genotype. In contrast,if the risk estimate (odds ratio or hazard ratio) for a particulargenotype is less than one, this indicates that an individual with thisparticular genotype has a reduced risk for the disease compared with anindividual who has the reference genotype.

With respect to drug response (e.g., response to a statin such aspravastatin), if the risk estimate (odds ratio or hazard ratio) of aparticular genotype is less than one, this indicates that an individualwith this particular genotype would benefit from the drug (an odds ratioor hazard ratio equal to one would indicate that the drug has noeffect). As used herein, the term “benefit” (with respect to a drug) isdefined as achieving a reduced risk for a disease that the drug isintended to treat or prevent (e.g., a CHD event such as MI) byadministrating the drug treatment, compared with the risk for thedisease in the absence of receiving the drug treatment (or receiving aplacebo in lieu of the drug treatment) for the same genotype.

For risk and drug response associations based on samples from the CARE,WOSCOPS, and PROSPER trials described herein, risk is assessed bycomparing the risk of CHD (e.g., MI) for a given genotype with the riskof CHD for a reference genotype in the placebo arm of the trial, anddrug response is assessed by comparing the risk of CHD (e.g., MI) in thepravastatin arm of the trial with the risk of CHD in the placebo arm ofthe trial for the same genotype.

In terms of risk, the KIF6 719Arg allele was associated with increasedrisk of CHD (e.g., MI) in samples from the CARE, WOSCOPS, and PROSPERtrials, as shown in the tables and described herein (particularly in theExamples). In terms of drug response, carriers of the KIF6 719Arg allelebenefited from pravastatin treatment in samples from the CARE, WOSCOPS,and PROSPER trials (whereas noncarriers did not benefit), as shown inthe tables and described herein (particularly in the Examples).

Following are descriptions of certain column headings that may be usedin any of Tables 5-22 (various derivatives of these headings may be usedas well).

Column Heading Definition Study CARE = ″Cholesterol and RecurrentEvents″ study. WOSCOPS = ″West of Scotland Coronary Prevention Study″.PROSPER = ″Prospective Study of Pravastatin in the Elderly at Risk″study. PROVE-IT = ″Pravastatin or Atorvastatin Evaluation and InfectionTherapy″ study. PROVE-IT-TIMI = ″Pravastatin or Atorvastatin Evaluationand Infection Therapy-Thrombolysis in Myocardial Infraction″ study.Strata Subpopulation used for analysis (e.g., placebo- orpravastatin-treated, or all patients unstratified by treatment). AllCount, Case Count, Cont Number of individuals analyzed in each study,separated Count into Case and Control groups according to individualshaving the disorder (cases) or not having the disorder (controls), orALL samples combined. Depending on the particular study (as explained inthe Examples section and/or in the Description of Tables section), thedisorder may be CHD (such as MI or recurrent MI) or aneurysm/dissection.Allele Particular SNP variant (nucleotide) investigated. Case Freq, ContFreq Total number of chromosomes with each allele in each study, dividedby twice the total number of individuals tested (i.e., two alleles perindividual) for Cases or Controls. Major Allele Major = high frequencyallele. Minor Allele Minor = rare (low frequency) allele. Genot Diploidgenotypes present for this SNP. Major homozygotes (″Maj Hom″)Individuals with 0 rare alleles. Minor homozygotes (″Min Hom″) Carriersof 2 rare alleles. Heterozygotes (″Het″) Carriers of 1 rare allele. Majhom + Het Individuals with 0 or 1 rare allele. Het + Min hom Allcarriers of 1 or 2 rare alleles. Dom Dominant model (minor homozygoteplus heterozygote vs major homozygote). Rec Recessive model (minorhomozygote vs heterozygote plus major homozygote). OR (min hom vs majhom) Minor homozygotes OR: odds ratio for a carrier with 2 rare alleles,using individuals with 0 rare alleles as a reference. OR (het vs majhom) Heterozygotes OR: odds ratio for a carrier with 1 rare allele,using individuals with 0 rare alleles as a reference. OR (Dom) DominantOR: odds ratio for a carrier with 1 or 2 rare alleles, using individualswith 0 rare alleles as a reference. OR (Rec) Recessive OR: odds ratiofor a carrier with 2 rare alleles, using individuals with 0 or 1 rarealleles as a reference. Allelic OR Odds ratio in those individuals withgenotypes possessing the rare allele vs. individuals with no rareallele. HW(ALL)pExact or Hardy-Weinberg expectations using an exact test(e.g., HW(Control)pExact for all individuals in the study, or just forcontrols). allelicAsc pExact Allelic association results using an exacttest. BDpvalue Breslow-Day p-value. Breslow-Day statistic tests the nullhypothesis of homogeneous odds ratio.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides SNPs associated with coronary heartdisease (CHD), particularly myocardial infarction (MI), as well asaneurysm/dissection, and SNPs that are associated with an individual'sresponsiveness to therapeutic agents, particularly statins, which may beused for the treatment (including preventive treatment) of CHD andaneurysm/dissection. The present invention further provides nucleic acidmolecules containing SNPs, methods and reagents for the detection of theSNPs disclosed herein, uses of these SNPs for the development ofdetection reagents, and assays or kits that utilize such reagents. TheSNPs disclosed herein are useful for diagnosing, prognosing, screeningfor, and evaluating predisposition to CHD, aneurysm/dissection, andrelated pathologies in humans. The drug response-associated SNPsdisclosed herein are particularly useful for predicting, screening for,and evaluating response to statin treatment, particularly treatment orprevention of CHD and aneurysm/dissection using statins, in humans.Furthermore, such SNPs and their encoded products are useful targets forthe development of therapeutic and preventive agents.

Furthermore, the drug response-associated SNPs disclosed herein are alsouseful for predicting an individual's responsiveness to drugs other thanstatins that are used to treat or prevent CHD or aneurysm/dissection,and these SNPs are also useful for predicting an individual'sresponsiveness to statins for the treatment or prevention of disordersother than CHD or aneurysm/dissection, particularly cancer. For example,the use of statins in the treatment of cancer is reviewed in: Hindler etal., “The role of statins in cancer therapy”, Oncologist. 2006 March;11(3):306-15; Demierre et al., “Statins and cancer prevention”, Nat RevCancer. 2005 December; 5(12):930-42; Stamm et al., “The role of statinsin cancer prevention and treatment”, Oncology. 2005 May; 19(6):739-50;and Sleijfer et al., “The potential of statins as part of anti-cancertreatment”, Eur J Cancer. 2005 March; 41(4):516-22, each of which isincorporated herein by reference in their entirety.

A large number of SNPs have been identified from re-sequencing DNA from39 individuals, and they are indicated as “Applera” SNP source in Tables1-2. Their allele frequencies observed in each of the Caucasian andAfrican-American ethnic groups are provided. Additional SNPs includedherein were previously identified during “shotgun” sequencing andassembly of the human genome, and they are indicated as “Celera” SNPsource in Tables 1 and 2. Furthermore, the information provided inTables 1 and 2, particularly the allele frequency information obtainedfrom 39 individuals and the identification of the precise position ofeach SNP within each gene/transcript, allows haplotypes (i.e., groups ofSNPs that are co-inherited) to be readily inferred. The presentinvention encompasses SNP haplotypes, as well as individual SNPs.

Thus, the present invention provides individual SNPs associated with CHD(particularly MI), aneurysm/dissection, and/or drug response(particularly statin response), as well as combinations of SNPs andhaplotypes, polymorphic/variant transcript sequences (SEQ ID NO: 1) andgenomic sequences (SEQ ID NOS: 4-9) containing SNPs, encoded amino acidsequences (SEQ ID NO: 2), and both transcript-based SNP contextsequences (SEQ ID NO: 3) and genomic-based SNP context sequences (SEQ IDNOS: 10-132) (transcript sequences, protein sequences, andtranscript-based SNP context sequences are provided in Table 1 and theSequence Listing; genomic sequences and genomic-based SNP contextsequences are provided in Table 2 and the Sequence Listing), methods ofdetecting these polymorphisms in a test sample, methods of determiningthe risk of an individual of having or developing CHD oraneurysm/dissection, methods of determining if an individual is likelyto respond to a particular treatment such as statins (particularly fortreating or preventing CHD or aneurysm/dissection), methods of screeningfor compounds useful for treating disorders associated with a variantgene/protein such as CHD or aneurysm/dissection, compounds identified bythese screening methods, methods of using the disclosed SNPs to select atreatment/preventive strategy or therapeutic agent, methods of treatingor preventing a disorder associated with a variant gene/protein, andmethods of using the SNPs of the present invention for humanidentification.

The present invention further provides methods for selecting orformulating a treatment regimen (e.g., methods for determining whetheror not to administer statin treatment to an individual having CHD oraneurysm/dissection, or who is at risk for developing CHD oraneurysm/dissection in the future, or who has previously had CHD oraneurysm/dissection, methods for selecting a particular statin-basedtreatment regimen such as dosage and frequency of administration ofstatin, or a particular form/type of statin such as a particularpharmaceutical formulation or statin compound, methods for administeringan alternative, non-statin-based treatment to individuals who arepredicted to be unlikely to respond positively to statin treatment,etc.), and methods for determining the likelihood of experiencingtoxicity or other undesirable side effects from statin treatment, etc.The present invention also provides methods for selecting individuals towhom a statin or other therapeutic will be administered based on theindividual's genotype, and methods for selecting individuals for aclinical trial of a statin or other therapeutic agent based on thegenotypes of the individuals (e.g., selecting individuals to participatein the trial who are most likely to respond positively from the statintreatment and/or excluding individuals from the trial who are unlikelyto respond positively from the statin treament).

The present invention provides novel SNPs associated with CHD,aneurysm/dissection, and/or response to statin treatment, as well asSNPs that were previously known in the art, but were not previouslyknown to be associated with CHD, aneurysm/dissection, or response tostatin treatment. Accordingly, the present invention provides novelcompositions and methods based on the novel SNPs disclosed herein, andalso provides novel methods of using the known, but previouslyunassociated, SNPs in methods relating to evaluating an individual'slikelihood of having or developing CHD (particularly MI) oraneurysm/dissection, predicting the likelihood of an individualexperiencing a reoccurrence of CHD (e.g., experiencing a recurrent MI)or aneurysm/dissection, prognosing the severity of CHD oraneurysm/dissection in an individual, or prognosing an individual'srecovery from CHD or aneurysm/dissection, and methods relating toevaluating an individual's likelihood of responding to statin treatment(particularly statin treatment, including preventive treatment, of CHDor aneurysm/dissection). In Tables 1 and 2, known SNPs are identifiedbased on the public database in which they have been observed, which isindicated as one or more of the following SNP types: “dbSNP”=SNPobserved in dbSNP, “HGBASE”=SNP observed in HGBASE, and “HGMD”=SNPobserved in the Human Gene Mutation Database (HGMD).

Particular SNP alleles of the present invention can be associated witheither an increased risk of having or developing CHD (e.g., MI) oraneurysm/dissection or increased likelihood of responding to statintreatment (particularly statin treatment, including preventivetreatment, of CHD or aneurysm/dissection), or a decreased risk of havingor developing CHD or aneurysm/dissection or decreased likelihood ofresponding to statin treatment. Thus, whereas certain SNPs (or theirencoded products) can be assayed to determine whether an individualpossesses a SNP allele that is indicative of an increased risk of havingor developing CHD (e.g., MI) or aneurysm/dissection or increasedlikelihood of responding to statin treatment, other SNPs (or theirencoded products) can be assayed to determine whether an individualpossesses a SNP allele that is indicative of a decreased risk of havingor developing CHD or aneurysm/dissection or decreased likelihood ofresponding to statin treatment. Similarly, particular SNP alleles of thepresent invention can be associated with either an increased ordecreased likelihood of having a reoccurrence of CHD (e.g., recurrentMI) or aneurysm/dissection, of fully recovering from CHD oraneurysm/dissection, of experiencing toxic effects from a particulartreatment or therapeutic compound, etc. The term “altered” may be usedherein to encompass either of these two possibilities (e.g., anincreased or a decreased risk/likelihood). SNP alleles that areassociated with a decreased risk of having or developing CHD (such asMI) or aneurysm/dissection may be referred to as “protective” alleles,and SNP alleles that are associated with an increased risk of having ordeveloping CHD or aneurysm/dissection may be referred to as“susceptibility” alleles, “risk” alleles, or “risk factors”.

Those skilled in the art will readily recognize that nucleic acidmolecules may be double-stranded molecules and that reference to aparticular site on one strand refers, as well, to the corresponding siteon a complementary strand. In defining a SNP position, SNP allele, ornucleotide sequence, reference to an adenine, a thymine (uridine), acytosine, or a guanine at a particular site on one strand of a nucleicacid molecule also defines the thymine (uridine), adenine, guanine, orcytosine (respectively) at the corresponding site on a complementarystrand of the nucleic acid molecule. Thus, reference may be made toeither strand in order to refer to a particular SNP position, SNPallele, or nucleotide sequence. Probes and primers, may be designed tohybridize to either strand and SNP genotyping methods disclosed hereinmay generally target either strand. Throughout the specification, inidentifying a SNP position, reference is generally made to theprotein-encoding strand, only for the purpose of convenience.

References to variant peptides, polypeptides, or proteins of the presentinvention include peptides, polypeptides, proteins, or fragmentsthereof, that contain at least one amino acid residue that differs fromthe corresponding amino acid sequence of the art-knownpeptide/polypeptide/protein (the art-known protein may beinterchangeably referred to as the “wild-type,” “reference,” or “normal”protein). Such variant peptides/polypeptides/proteins can result from acodon change caused by a nonsynonymous nucleotide substitution at aprotein-coding SNP position (i.e., a missense mutation) disclosed by thepresent invention. Variant peptides/polypeptides/proteins of the presentinvention can also result from a nonsense mutation (i.e., a SNP thatcreates a premature stop codon, a SNP that generates a read-throughmutation by abolishing a stop codon), or due to any SNP disclosed by thepresent invention that otherwise alters the structure, function,activity, or expression of a protein, such as a SNP in a regulatoryregion (e.g. a promoter or enhancer) or a SNP that leads to alternativeor defective splicing, such as a SNP in an intron or a SNP at anexon/intron boundary. As used herein, the terms “polypeptide,”“peptide,” and “protein” are used interchangeably.

As used herein, an “allele” may refer to a nucleotide at a SNP position(wherein at least two alternative nucleotides are present in thepopulation at the SNP position, in accordance with the inherentdefinition of a SNP) or may refer to an amino acid residue that isencoded by the codon which contains the SNP position (where thealternative nucleotides that are present in the population at the SNPposition form alternative codons that encode different amino acidresidues). Using the KIF6 SNP (hCV3054799/rs20455) as an example, theterm “allele” can refer to, for example, an ‘A’ or ‘G’ nucleotide (orthe reverse complements thereof) at the SNP position, or a tryptophan(Trp) or arginine (Arg) residue at amino acid position 719 of the KIF6protein. An “allele” may also be referred to herein as a “variant”.Also, an amino acid residue that is encoded by a codon containing aparticular SNP may simply be referred to as being encoded by the SNP.

The results of a test (e.g., an individual's risk for CHD oraneurysm/dissection, or an individual's predicted drug responsiveness,based on assaying one or more SNPs disclosed herein, and/or anindividual's genotype for one or more SNPs disclosed herein, etc.),and/or any other information pertaining to a test, may be referred toherein as a “report”. A tangible report can optionally be generated aspart of a testing process (which may be interchangeably referred toherein as “reporting”, or as “providing” a report, “producing” a report,or “generating” a report). Examples of tangible reports may include, butare not limited to, reports in paper (such as computer-generatedprintouts of test results) or equivalent formats and reports stored oncomputer readable medium (such as a CD, computer hard drive, or computernetwork server, etc.). Reports, particularly those stored on computerreadable medium, can be part of a database (such as a database ofpatient records, which may be a “secure database” that has securityfeatures that limit access to the report, such as to allow only thepatient and the patient's medical practioners to view the report, forexample). In addition to, or as an alternative to, generating a tangiblereport, reports can also be displayed on a computer screen (or thedisplay of another electronic device or instrument).

A report can further be “transmitted” or “communicated” (these terms maybe used herein interchangeably), such as to the individual who wastested, a medical practitioner (e.g., a doctor, nurse, clinicallaboratory practitioner, genetic counselor, etc.), a healthcareorganization, a clinical laboratory, and/or any other party intended toview or possess the report. The act of “transmitting” or “communicating”a report can be by any means known in the art, based on the form of thereport. Furthermore, “transmitting” or “communicating” a report caninclude delivering a report (“pushing”) and/or retrieving (“pulling”) areport. For example, reports can be transmitted/communicated by suchmeans as being physically transferred between parties (such as forreports in paper format), such as by being physically delivered from oneparty to another, or by being transmitted electronically or in signalform (e.g., via e-mail or over the internet, by facsimile, and/or by anywired or wireless communication methods known in the art), such as bybeing retrieved from a database stored on a computer network server,etc.

Isolated Nucleic Acid Molecules and SNP Detection Reagents &

Kits

Tables 1 and 2 provide a variety of information about each SNP of thepresent invention that is associated with CHD (particularly MI),aneurysm/dissection, and/or drug response (particularly response tostatin treatment), including the transcript sequences (SEQ ID NO: 1),genomic sequences (SEQ ID NOS: 4-9), and protein sequences (SEQ ID NO:2) of the encoded gene products (with the SNPs indicated by IUB codes inthe nucleic acid sequences). In addition, Tables 1 and 2 include SNPcontext sequences, which generally include 100 nucleotide upstream (5′)plus 100 nucleotides downstream (3′) of each SNP position (SEQ ID NO: 3correspond to transcript-based SNP context sequences disclosed in Table1, and SEQ ID NOS: 10-132 correspond to genomic-based context sequencesdisclosed in Table 2), the alternative nucleotides (alleles) at each SNPposition, and additional information about the variant where relevant,such as SNP type (coding, missense, splice site, UTR, etc.), humanpopulations in which the SNP was observed, observed allele frequencies,information about the encoded protein, etc.

Isolated Nucleic Acid Molecules

The present invention provides isolated nucleic acid molecules thatcontain one or more SNPs disclosed Table 1 and/or Table 2. Isolatednucleic acid molecules containing one or more SNPs disclosed in at leastone of Tables 1 and 2 may be interchangeably referred to throughout thepresent text as “SNP-containing nucleic acid molecules.” Isolatednucleic acid molecules may optionally encode a full-length variantprotein or fragment thereof. The isolated nucleic acid molecules of thepresent invention also include probes and primers (which are describedin greater detail below in the section entitled “SNP DetectionReagents”), which may be used for assaying the disclosed SNPs, andisolated full-length genes, transcripts, cDNA molecules, and fragmentsthereof, which may be used for such purposes as expressing an encodedprotein.

As used herein, an “isolated nucleic acid molecule” generally is onethat contains a SNP of the present invention or one that hybridizes tosuch molecule such as a nucleic acid with a complementary sequence, andis separated from most other nucleic acids present in the natural sourceof the nucleic acid molecule. Moreover, an “isolated” nucleic acidmolecule, such as a cDNA molecule containing a SNP of the presentinvention, can be substantially free of other cellular material, orculture medium when produced by recombinant techniques, or chemicalprecursors or other chemicals when chemically synthesized. A nucleicacid molecule can be fused to other coding or regulatory sequences andstill be considered “isolated.” Nucleic acid molecules present innon-human transgenic animals, which do not naturally occur in theanimal, are also considered “isolated.” For example, recombinant DNAmolecules contained in a vector are considered “isolated.” Furtherexamples of “isolated” DNA molecules include recombinant DNA moleculesmaintained in heterologous host cells, and purified (partially orsubstantially) DNA molecules in solution. Isolated RNA molecules includein vivo or in vitro RNA transcripts of the isolated SNP-containing DNAmolecules of the present invention. Isolated nucleic acid moleculesaccording to the present invention further include such moleculesproduced synthetically.

Generally, an isolated SNP-containing nucleic acid molecule comprisesone or more SNP positions disclosed by the present invention withflanking nucleotide sequences on either side of the SNP positions. Aflanking sequence can include nucleotide residues that are naturallyassociated with the SNP site and/or heterologous nucleotide sequences.Preferably, the flanking sequence is up to about 500, 300, 100, 60, 50,30, 25, 20, 15, 10, 8, or 4 nucleotides (or any other length in-between)on either side of a SNP position, or as long as the full-length gene orentire protein-coding sequence (or any portion thereof such as an exon),especially if the SNP-containing nucleic acid molecule is to be used toproduce a protein or protein fragment.

For full-length genes and entire protein-coding sequences, a SNPflanking sequence can be, for example, up to about 5 KB, 4 KB, 3 KB, 2KB, 1 KB on either side of the SNP. Furthermore, in such instances theisolated nucleic acid molecule comprises exonic sequences (includingprotein-coding and/or non-coding exonic sequences), but may also includeintronic sequences. Thus, any protein coding sequence may be eithercontiguous or separated by introns. The important point is that thenucleic acid is isolated from remote and unimportant flanking sequencesand is of appropriate length such that it can be subjected to thespecific manipulations or uses described herein such as recombinantprotein expression, preparation of probes and primers for assaying theSNP position, and other uses specific to the SNP-containing nucleic acidsequences.

An isolated SNP-containing nucleic acid molecule can comprise, forexample, a full-length gene or transcript, such as a gene isolated fromgenomic DNA (e.g., by cloning or PCR amplification), a cDNA molecule, oran mRNA transcript molecule. Polymorphic transcript sequences arereferred to in Table 1 and provided in the Sequence Listing (SEQ ID NO:1), and polymorphic genomic sequences are referred to in Table 2 andprovided in the Sequence Listing (SEQ ID NOS: 4-9). Furthermore,fragments of such full-length genes and transcripts that contain one ormore SNPs disclosed herein are also encompassed by the presentinvention, and such fragments may be used, for example, to express anypart of a protein, such as a particular functional domain or anantigenic epitope.

Thus, the present invention also encompasses fragments of the nucleicacid sequences as disclosed in Tables 1 and 2 (transcript sequences arereferred to in Table 1 as SEQ ID NO: 1, genomic sequences are referredto in Table 2 as SEQ ID NOS: 4-9, transcript-based SNP context sequencesare referred to in Table 1 as SEQ ID NO: 3, and genomic-based SNPcontext sequences are referred to in Table 2 as SEQ ID NOS: 10-132) andtheir complements. The actual sequences referred to in the tables areprovided in the Sequence Listing. A fragment typically comprises acontiguous nucleotide sequence at least about 8 or more nucleotides,more preferably at least about 12 or more nucleotides, and even morepreferably at least about 16 or more nucleotides. Furthermore, afragment could comprise at least about 18, 20, 22, 25, 30, 40, 50, 60,80, 100, 150, 200, 250 or 500 nucleotides in length (or any other numberin between). The length of the fragment will be based on its intendeduse. For example, the fragment can encode epitope-bearing regions of avariant peptide or regions of a variant peptide that differ from thenormal/wild-type protein, or can be useful as a polynucleotide probe orprimer. Such fragments can be isolated using the nucleotide sequencesprovided in Table 1 and/or Table 2 for the synthesis of a polynucleotideprobe. A labeled probe can then be used, for example, to screen a cDNAlibrary, genomic DNA library, or mRNA to isolate nucleic acidcorresponding to the coding region. Further, primers can be used inamplification reactions, such as for purposes of assaying one or moreSNPs sites or for cloning specific regions of a gene.

An isolated nucleic acid molecule of the present invention furtherencompasses a SNP-containing polynucleotide that is the product of anyone of a variety of nucleic acid amplification methods, which are usedto increase the copy numbers of a polynucleotide of interest in anucleic acid sample. Such amplification methods are well known in theart, and they include but are not limited to, polymerase chain reaction(PCR) (U.S. Pat. Nos. 4,683,195 and 4,683,202; PCR Technology:Principles and Applications for DNA Amplification, ed. H. A. Erlich,Freeman Press, NY, NY (1992)), ligase chain reaction (LCR) (Wu andWallace, Genomics 4:560 (1989); Landegren et al., Science 241:1077(1988)), strand displacement amplification (SDA) (U.S. Pat. Nos.5,270,184 and 5,422,252), transcription-mediated amplification (TMA)(U.S. Pat. No. 5,399,491), linked linear amplification (LLA) (U.S. Pat.No. 6,027,923) and the like, and isothermal amplification methods suchas nucleic acid sequence based amplification (NASBA) and self-sustainedsequence replication (Guatelli et al., Proc Natl Acad Sci USA 87:1874(1990)). Based on such methodologies, a person skilled in the art canreadily design primers in any suitable regions 5′ and 3′ to a SNPdisclosed herein. Such primers may be used to amplify DNA of any lengthso long that it contains the SNP of interest in its sequence.

As used herein, an “amplified polynucleotide” of the invention is aSNP-containing nucleic acid molecule whose amount has been increased atleast two fold by any nucleic acid amplification method performed invitro as compared to its starting amount in a test sample. In otherpreferred embodiments, an amplified polynucleotide is the result of atleast ten fold, fifty fold, one hundred fold, one thousand fold, or eventen thousand fold increase as compared to its starting amount in a testsample. In a typical PCR amplification, a polynucleotide of interest isoften amplified at least fifty thousand fold in amount over theunamplified genomic DNA, but the precise amount of amplification neededfor an assay depends on the sensitivity of the subsequent detectionmethod used.

Generally, an amplified polynucleotide is at least about 16 nucleotidesin length. More typically, an amplified polynucleotide is at least about20 nucleotides in length. In a preferred embodiment of the invention, anamplified polynucleotide is at least about 30 nucleotides in length. Ina more preferred embodiment of the invention, an amplifiedpolynucleotide is at least about 32, 40, 45, 50, or 60 nucleotides inlength. In yet another preferred embodiment of the invention, anamplified polynucleotide is at least about 100, 200, 300, 400, or 500nucleotides in length. While the total length of an amplifiedpolynucleotide of the invention can be as long as an exon, an intron orthe entire gene where the SNP of interest resides, an amplified productis typically up to about 1,000 nucleotides in length (although certainamplification methods may generate amplified products greater than 1000nucleotides in length). More preferably, an amplified polynucleotide isnot greater than about 600-700 nucleotides in length. It is understoodthat irrespective of the length of an amplified polynucleotide, a SNP ofinterest may be located anywhere along its sequence.

In a specific embodiment of the invention, the amplified product is atleast about 201 nucleotides in length, comprises one of thetranscript-based context sequences or the genomic-based contextsequences shown in Tables 1 and 2. Such a product may have additionalsequences on its 5′ end or 3′ end or both. In another embodiment, theamplified product is about 101 nucleotides in length, and it contains aSNP disclosed herein. Preferably, the SNP is located at the middle ofthe amplified product (e.g., at position 101 in an amplified productthat is 201 nucleotides in length, or at position 51 in an amplifiedproduct that is 101 nucleotides in length), or within 1, 2, 3, 4, 5, 6,7, 8, 9, 10, 12, 15, or 20 nucleotides from the middle of the amplifiedproduct. However, as indicated above, the SNP of interest may be locatedanywhere along the length of the amplified product.

The present invention provides isolated nucleic acid molecules thatcomprise, consist of, or consist essentially of one or morepolynucleotide sequences that contain one or more SNPs disclosed herein,complements thereof, and SNP-containing fragments thereof.

Accordingly, the present invention provides nucleic acid molecules thatconsist of any of the nucleotide sequences shown in Table 1 and/or Table2 (transcript sequences are referred to in Table 1 as SEQ ID NO: 1,genomic sequences are referred to in Table 2 as SEQ ID NOS: 4-9,transcript-based SNP context sequences are referred to in Table 1 as SEQID NO: 3, and genomic-based SNP context sequences are referred to inTable 2 as SEQ ID NOS: 10-132), or any nucleic acid molecule thatencodes any of the variant proteins referred to in Table 1 (SEQ ID NO:2). The actual sequences referred to in the tables are provided in theSequence Listing. A nucleic acid molecule consists of a nucleotidesequence when the nucleotide sequence is the complete nucleotidesequence of the nucleic acid molecule.

The present invention further provides nucleic acid molecules thatconsist essentially of any of the nucleotide sequences referred to inTable 1 and/or Table 2 (transcript sequences are referred to in Table 1as SEQ ID NO: 1, genomic sequences are referred to in Table 2 as SEQ IDNOS: 4-9, transcript-based SNP context sequences are referred to inTable 1 as SEQ ID NO: 3, and genomic-based SNP context sequences arereferred to in Table 2 as SEQ ID NOS: 10-132), or any nucleic acidmolecule that encodes any of the variant proteins referred to in Table 1(SEQ ID NO: 2). The actual sequences referred to in the tables areprovided in the Sequence Listing. A nucleic acid molecule consistsessentially of a nucleotide sequence when such a nucleotide sequence ispresent with only a few additional nucleotide residues in the finalnucleic acid molecule.

The present invention further provides nucleic acid molecules thatcomprise any of the nucleotide sequences shown in Table 1 and/or Table 2or a SNP-containing fragment thereof (transcript sequences are referredto in Table 1 as SEQ ID NO: 1, genomic sequences are referred to inTable 2 as SEQ ID NOS: 4-9, transcript-based SNP context sequences arereferred to in Table 1 as SEQ ID NO: 3, and genomic-based SNP contextsequences are referred to in Table 2 as SEQ ID NOS: 10-132), or anynucleic acid molecule that encodes any of the variant proteins providedin Table 1 (SEQ ID NO: 2). The actual sequences referred to in thetables are provided in the Sequence Listing. A nucleic acid moleculecomprises a nucleotide sequence when the nucleotide sequence is at leastpart of the final nucleotide sequence of the nucleic acid molecule. Insuch a fashion, the nucleic acid molecule can be only the nucleotidesequence or have additional nucleotide residues, such as residues thatare naturally associated with it or heterologous nucleotide sequences.Such a nucleic acid molecule can have one to a few additionalnucleotides or can comprise many more additional nucleotides. A briefdescription of how various types of these nucleic acid molecules can bereadily made and isolated is provided below, and such techniques arewell known to those of ordinary skill in the art. Sambrook and Russell,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, N.Y.(2000).

The isolated nucleic acid molecules can encode mature proteins plusadditional amino or carboxyl-terminal amino acids or both, or aminoacids interior to the mature peptide (when the mature form has more thanone peptide chain, for instance). Such sequences may play a role inprocessing of a protein from precursor to a mature form, facilitateprotein trafficking, prolong or shorten protein half-life, or facilitatemanipulation of a protein for assay or production. As generally is thecase in situ, the additional amino acids may be processed away from themature protein by cellular enzymes.

Thus, the isolated nucleic acid molecules include, but are not limitedto, nucleic acid molecules having a sequence encoding a peptide alone, asequence encoding a mature peptide and additional coding sequences suchas a leader or secretory sequence (e.g., a pre-pro or pro-proteinsequence), a sequence encoding a mature peptide with or withoutadditional coding sequences, plus additional non-coding sequences, forexample introns and non-coding 5′ and 3′ sequences such as transcribedbut untranslated sequences that play a role in, for example,transcription, mRNA processing (including splicing and polyadenylationsignals), ribosome binding, and/or stability of mRNA. In addition, thenucleic acid molecules may be fused to heterologous marker sequencesencoding, for example, a peptide that facilitates purification.

Isolated nucleic acid molecules can be in the form of RNA, such as mRNA,or in the form DNA, including cDNA and genomic DNA, which may beobtained, for example, by molecular cloning or produced by chemicalsynthetic techniques or by a combination thereof. Sambrook and Russell,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, N.Y.(2000). Furthermore, isolated nucleic acid molecules, particularly SNPdetection reagents such as probes and primers, can also be partially orcompletely in the form of one or more types of nucleic acid analogs,such as peptide nucleic acid (PNA). U.S. Pat. Nos. 5,539,082; 5,527,675;5,623,049; and 5,714,331. The nucleic acid, especially DNA, can bedouble-stranded or single-stranded. Single-stranded nucleic acid can bethe coding strand (sense strand) or the complementary non-coding strand(anti-sense strand). DNA, RNA, or PNA segments can be assembled, forexample, from fragments of the human genome (in the case of DNA or RNA)or single nucleotides, short oligonucleotide linkers, or from a seriesof oligonucleotides, to provide a synthetic nucleic acid molecule.Nucleic acid molecules can be readily synthesized using the sequencesprovided herein as a reference; oligonucleotide and PNA oligomersynthesis techniques are well known in the art. See, e.g., Corey,“Peptide nucleic acids: expanding the scope of nucleic acidrecognition,” Trends Biotechnol 15(6):224-9 (June 1997), and Hyrup etal., “Peptide nucleic acids (PNA): synthesis, properties and potentialapplications,” Bioorg Med Chem 4(1):5-23) (January 1996). Furthermore,large-scale automated oligonucleotide/PNA synthesis (including synthesison an array or bead surface or other solid support) can readily beaccomplished using commercially available nucleic acid synthesizers,such as the Applied Biosystems (Foster City, Calif.) 3900High-Throughput DNA Synthesizer or Expedite 8909 Nucleic Acid SynthesisSystem, and the sequence information provided herein.

The present invention encompasses nucleic acid analogs that containmodified, synthetic, or non-naturally occurring nucleotides orstructural elements or other alternative/modified nucleic acidchemistries known in the art. Such nucleic acid analogs are useful, forexample, as detection reagents (e.g., primers/probes) for detecting oneor more SNPs identified in Table 1 and/or Table 2. Furthermore,kits/systems (such as beads, arrays, etc.) that include these analogsare also encompassed by the present invention. For example, PNAoligomers that are based on the polymorphic sequences of the presentinvention are specifically contemplated. PNA oligomers are analogs ofDNA in which the phosphate backbone is replaced with a peptide-likebackbone. Lagriffoul et al., Bioorganic & Medicinal Chemistry Letters4:1081-1082 (1994); Petersen et al., Bioorganic & Medicinal ChemistryLetters 6:793-796 (1996); Kumar et al., Organic Letters 3(9):1269-1272(2001); WO 96/04000. PNA hybridizes to complementary RNA or DNA withhigher affinity and specificity than conventional oligonucleotides andoligonucleotide analogs. The properties of PNA enable novel molecularbiology and biochemistry applications unachievable with traditionaloligonucleotides and peptides.

Additional examples of nucleic acid modifications that improve thebinding properties and/or stability of a nucleic acid include the use ofbase analogs such as inosine, intercalators (U.S. Pat. No. 4,835,263)and the minor groove binders (U.S. Pat. No. 5,801,115). Thus, referencesherein to nucleic acid molecules, SNP-containing nucleic acid molecules,SNP detection reagents (e.g., probes and primers),oligonucleotides/polynucleotides include PNA oligomers and other nucleicacid analogs. Other examples of nucleic acid analogs andalternative/modified nucleic acid chemistries known in the art aredescribed in Current Protocols in Nucleic Acid Chemistry, John Wiley &Sons, N.Y. (2002).

The present invention further provides nucleic acid molecules thatencode fragments of the variant polypeptides disclosed herein as well asnucleic acid molecules that encode obvious variants of such variantpolypeptides. Such nucleic acid molecules may be naturally occurring,such as paralogs (different locus) and orthologs (different organism),or may be constructed by recombinant DNA methods or by chemicalsynthesis. Non-naturally occurring variants may be made by mutagenesistechniques, including those applied to nucleic acid molecules, cells, ororganisms. Accordingly, the variants can contain nucleotidesubstitutions, deletions, inversions and insertions (in addition to theSNPs disclosed in Tables 1 and 2). Variation can occur in either or boththe coding and non-coding regions. The variations can produceconservative and/or non-conservative amino acid substitutions.

Further variants of the nucleic acid molecules disclosed in Tables 1 and2, such as naturally occurring allelic variants (as well as orthologsand paralogs) and synthetic variants produced by mutagenesis techniques,can be identified and/or produced using methods well known in the art.Such further variants can comprise a nucleotide sequence that shares atleast 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or99% sequence identity with a nucleic acid sequence disclosed in Table 1and/or Table 2 (or a fragment thereof) and that includes a novel SNPallele disclosed in Table 1 and/or Table 2. Further, variants cancomprise a nucleotide sequence that encodes a polypeptide that shares atleast 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or99% sequence identity with a polypeptide sequence disclosed in Table 1(or a fragment thereof) and that includes a novel SNP allele disclosedin Table 1 and/or Table 2. Thus, an aspect of the present invention thatis specifically contemplated are isolated nucleic acid molecules thathave a certain degree of sequence variation compared with the sequencesshown in Tables 1-2, but that contain a novel SNP allele disclosedherein. In other words, as long as an isolated nucleic acid moleculecontains a novel SNP allele disclosed herein, other portions of thenucleic acid molecule that flank the novel SNP allele can vary to somedegree from the specific transcript, genomic, and context sequencesreferred to and shown in Tables 1 and 2, and can encode a polypeptidethat varies to some degree from the specific polypeptide sequencesreferred to in Table 1.

To determine the percent identity of two amino acid sequences or twonucleotide sequences of two molecules that share sequence homology, thesequences are aligned for optimal comparison purposes (e.g., gaps can beintroduced in one or both of a first and a second amino acid or nucleicacid sequence for optimal alignment and non-homologous sequences can bedisregarded for comparison purposes). In a preferred embodiment, atleast 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the length of areference sequence is aligned for comparison purposes. The amino acidresidues or nucleotides at corresponding amino acid positions ornucleotide positions are then compared. When a position in the firstsequence is occupied by the same amino acid residue or nucleotide as thecorresponding position in the second sequence, then the molecules areidentical at that position (as used herein, amino acid or nucleic acid“identity” is equivalent to amino acid or nucleic acid “homology”). Thepercent identity between the two sequences is a function of the numberof identical positions shared by the sequences, taking into account thenumber of gaps, and the length of each gap, which need to be introducedfor optimal alignment of the two sequences.

The comparison of sequences and determination of percent identitybetween two sequences can be accomplished using a mathematicalalgorithm. Computational Molecular Biology, A. M. Lesk, ed., OxfordUniversity Press, N.Y (1988); Biocomputing: Informatics and GenomeProjects, D. W. Smith, ed., Academic Press, N.Y. (1993); ComputerAnalysis of Sequence Data, Part 1, A. M. Griffin and H. G. Griffin,eds., Humana Press, N.J. (1994); Sequence Analysis in Molecular Biology,G. von Heinje, ed., Academic Press, N.Y. (1987); and Sequence AnalysisPrimer, M. Gribskov and J. Devereux, eds., M. Stockton Press, N.Y.(1991). In a preferred embodiment, the percent identity between twoamino acid sequences is determined using the Needleman and Wunschalgorithm (J Mol Biol (48):444-453 (1970)) which has been incorporatedinto the GAP program in the GCG software package, using either a Blossom62 matrix or a PAM250 matrix, and a gap weight of 16, 14, 12, 10, 8, 6,or 4 and a length weight of 1, 2, 3, 4, 5, or 6.

In yet another preferred embodiment, the percent identity between twonucleotide sequences is determined using the GAP program in the GCGsoftware package using a NWSgapdna.CMP matrix and a gap weight of 40,50, 60, 70, or 80 and a length weight of 1, 2, 3, 4, 5, or 6. J.Devereux et al., Nucleic Acids Res. 12(1):387 (1984). In anotherembodiment, the percent identity between two amino acid or nucleotidesequences is determined using the algorithm of E. Myers and W. Miller(CABIOS 4:11-17 (1989)) which has been incorporated into the ALIGNprogram (version 2.0), using a PAM120 weight residue table, a gap lengthpenalty of 12, and a gap penalty of 4.

The nucleotide and amino acid sequences of the present invention canfurther be used as a “query sequence” to perform a search againstsequence databases; for example, to identify other family members orrelated sequences. Such searches can be performed using the NBLAST andXBLAST programs (version 2.0). Altschul et al., J Mol Biol 215:403-10(1990). BLAST nucleotide searches can be performed with the NBLASTprogram, score=100, wordlength=12 to obtain nucleotide sequenceshomologous to the nucleic acid molecules of the invention. BLAST proteinsearches can be performed with the XBLAST program, score=50,wordlength=3 to obtain amino acid sequences homologous to the proteinsof the invention. To obtain gapped alignments for comparison purposes,Gapped BLAST can be utilized. Altschul et al., Nucleic Acids Res25(17):3389-3402 (1997). When utilizing BLAST and gapped BLAST programs,the default parameters of the respective programs (e.g., XBLAST andNBLAST) can be used. In addition to BLAST, examples of other search andsequence comparison programs used in the art include, but are notlimited to, FASTA (Pearson, Methods Mol Biol 25, 365-389 (1994)) andKERR (Dufresne et al., Nat Biotechnol 20(12): 1269-71 (December 2002)).For further information regarding bioinformatics techniques, see CurrentProtocols in Bioinformatics, John Wiley & Sons, Inc., N.Y.

The present invention further provides non-coding fragments of thenucleic acid molecules disclosed in Table 1 and/or Table 2. Preferrednon-coding fragments include, but are not limited to, promotersequences, enhancer sequences, intronic sequences, 5′ untranslatedregions (UTRs), 3′ untranslated regions, gene modulating sequences andgene termination sequences. Such fragments are useful, for example, incontrolling heterologous gene expression and in developing screens toidentify gene-modulating agents.

SNP Detection Reagents

In a specific aspect of the present invention, the SNPs disclosed inTable 1 and/or Table 2, and their associated transcript sequences(referred to in Table 1 as SEQ ID NO: 1), genomic sequences (referred toin Table 2 as SEQ ID NOS: 4-9), and context sequences (transcript-basedcontext sequences are referred to in Table 1 as SEQ ID NO: 3;genomic-based context sequences are provided in Table 2 as SEQ ID NOS:10-132), can be used for the design of SNP detection reagents. Theactual sequences referred to in the tables are provided in the SequenceListing. As used herein, a “SNP detection reagent” is a reagent thatspecifically detects a specific target SNP position disclosed herein,and that is preferably specific for a particular nucleotide (allele) ofthe target SNP position (i.e., the detection reagent preferably candifferentiate between different alternative nucleotides at a target SNPposition, thereby allowing the identity of the nucleotide present at thetarget SNP position to be determined). Typically, such detection reagenthybridizes to a target SNP-containing nucleic acid molecule bycomplementary base-pairing in a sequence specific manner, anddiscriminates the target variant sequence from other nucleic acidsequences such as an art-known form in a test sample. An example of adetection reagent is a probe that hybridizes to a target nucleic acidcontaining one or more of the SNPs referred to in Table 1 and/or Table2. In a preferred embodiment, such a probe can differentiate betweennucleic acids having a particular nucleotide (allele) at a target SNPposition from other nucleic acids that have a different nucleotide atthe same target SNP position. In addition, a detection reagent mayhybridize to a specific region 5′ and/or 3′ to a SNP position,particularly a region corresponding to the context sequences referred toin Table 1 and/or Table 2 (transcript-based context sequences arereferred to in Table 1 as SEQ ID NO: 3; genomic-based context sequencesare referred to in Table 2 as SEQ ID NOS: 10-132). Another example of adetection reagent is a primer that acts as an initiation point ofnucleotide extension along a complementary strand of a targetpolynucleotide. The SNP sequence information provided herein is alsouseful for designing primers, e.g. allele-specific primers, to amplify(e.g., using PCR) any SNP of the present invention.

In one preferred embodiment of the invention, a SNP detection reagent isan isolated or synthetic DNA or RNA polynucleotide probe or primer orPNA oligomer, or a combination of DNA, RNA and/or PNA, that hybridizesto a segment of a target nucleic acid molecule containing a SNPidentified in Table 1 and/or Table 2. A detection reagent in the form ofa polynucleotide may optionally contain modified base analogs,intercalators or minor groove binders. Multiple detection reagents suchas probes may be, for example, affixed to a solid support (e.g., arraysor beads) or supplied in solution (e.g. probe/primer sets for enzymaticreactions such as PCR, RT-PCR, TaqMan assays, or primer-extensionreactions) to form a SNP detection kit.

A probe or primer typically is a substantially purified oligonucleotideor PNA oligomer. Such oligonucleotide typically comprises a region ofcomplementary nucleotide sequence that hybridizes under stringentconditions to at least about 8, 10, 12, 16, 18, 20, 22, 25, 30, 40, 50,55, 60, 65, 70, 80, 90, 100, 120 (or any other number in-between) ormore consecutive nucleotides in a target nucleic acid molecule.Depending on the particular assay, the consecutive nucleotides caneither include the target SNP position, or be a specific region in closeenough proximity 5′ and/or 3′ to the SNP position to carry out thedesired assay.

Other preferred primer and probe sequences can readily be determinedusing the transcript sequences (SEQ ID NO: 1), genomic sequences (SEQ IDNOS: 4-9), and SNP context sequences (transcript-based context sequencesare referred to in Table 1 as SEQ ID NO:3; genomic-based contextsequences are referred to in Table 2 as SEQ ID NOS: 10-132) disclosed inthe Sequence Listing and in Tables 1 and 2. The actual sequencesreferred to in the tables are provided in the Sequence Listing. It willbe apparent to one of skill in the art that such primers and probes aredirectly useful as reagents for genotyping the SNPs of the presentinvention, and can be incorporated into any kit/system format.

In order to produce a probe or primer specific for a targetSNP-containing sequence, the gene/transcript and/or context sequencesurrounding the SNP of interest is typically examined using a computeralgorithm that starts at the 5′ or at the 3′ end of the nucleotidesequence. Typical algorithms will then identify oligomers of definedlength that are unique to the gene/SNP context sequence, have a GCcontent within a range suitable for hybridization, lack predictedsecondary structure that may interfere with hybridization, and/orpossess other desired characteristics or that lack other undesiredcharacteristics.

A primer or probe of the present invention is typically at least about 8nucleotides in length. In one embodiment of the invention, a primer or aprobe is at least about 10 nucleotides in length. In a preferredembodiment, a primer or a probe is at least about 12 nucleotides inlength. In a more preferred embodiment, a primer or probe is at leastabout 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 nucleotides in length.While the maximal length of a probe can be as long as the targetsequence to be detected, depending on the type of assay in which it isemployed, it is typically less than about 50, 60, 65, or 70 nucleotidesin length. In the case of a primer, it is typically less than about 30nucleotides in length. In a specific preferred embodiment of theinvention, a primer or a probe is within the length of about 18 andabout 28 nucleotides. However, in other embodiments, such as nucleicacid arrays and other embodiments in which probes are affixed to asubstrate, the probes can be longer, such as on the order of 30-70, 75,80, 90, 100, or more nucleotides in length (see the section belowentitled “SNP Detection Kits and Systems”).

For analyzing SNPs, it may be appropriate to use oligonucleotidesspecific for alternative SNP alleles. Such oligonucleotides that detectsingle nucleotide variations in target sequences may be referred to bysuch terms as “allele-specific oligonucleotides,” “allele-specificprobes,” or “allele-specific primers.” The design and use ofallele-specific probes for analyzing polymorphisms is described in,e.g., Mutation Detection: A Practical Approach, Cotton et al., eds.,Oxford University Press (1998); Saiki et al., Nature 324:163-166 (1986);Dattagupta, EP235,726; and Saiki, WO 89/11548.

While the design of each allele-specific primer or probe depends onvariables such as the precise composition of the nucleotide sequencesflanking a SNP position in a target nucleic acid molecule, and thelength of the primer or probe, another factor in the use of primers andprobes is the stringency of the condition under which the hybridizationbetween the probe or primer and the target sequence is performed. Higherstringency conditions utilize buffers with lower ionic strength and/or ahigher reaction temperature, and tend to require a more perfect matchbetween probe/primer and a target sequence in order to form a stableduplex. If the stringency is too high, however, hybridization may notoccur at all. In contrast, lower stringency conditions utilize bufferswith higher ionic strength and/or a lower reaction temperature, andpermit the formation of stable duplexes with more mismatched basesbetween a probe/primer and a target sequence. By way of example and notlimitation, exemplary conditions for high stringency hybridizationconditions using an allele-specific probe are as follows:prehybridization with a solution containing 5× standard saline phosphateEDTA (SSPE), 0.5% NaDodSO₄ (SDS) at 55° C., and incubating probe withtarget nucleic acid molecules in the same solution at the sametemperature, followed by washing with a solution containing 2×SSPE, and0.1% SDS at 55° C. or room temperature.

Moderate stringency hybridization conditions may be used forallele-specific primer extension reactions with a solution containing,e.g., about 50 mM KCl at about 46° C. Alternatively, the reaction may becarried out at an elevated temperature such as 60° C. In anotherembodiment, a moderately stringent hybridization condition suitable foroligonucleotide ligation assay (OLA) reactions wherein two probes areligated if they are completely complementary to the target sequence mayutilize a solution of about 100 mM KCl at a temperature of 46° C.

In a hybridization-based assay, allele-specific probes can be designedthat hybridize to a segment of target DNA from one individual but do nothybridize to the corresponding segment from another individual due tothe presence of different polymorphic forms (e.g., alternative SNPalleles/nucleotides) in the respective DNA segments from the twoindividuals. Hybridization conditions should be sufficiently stringentthat there is a significant detectable difference in hybridizationintensity between alleles, and preferably an essentially binaryresponse, whereby a probe hybridizes to only one of the alleles orsignificantly more strongly to one allele. While a probe may be designedto hybridize to a target sequence that contains a SNP site such that theSNP site aligns anywhere along the sequence of the probe, the probe ispreferably designed to hybridize to a segment of the target sequencesuch that the SNP site aligns with a central position of the probe(e.g., a position within the probe that is at least three nucleotidesfrom either end of the probe). This design of probe generally achievesgood discrimination in hybridization between different allelic forms.

In another embodiment, a probe or primer may be designed to hybridize toa segment of target DNA such that the SNP aligns with either the 5′ mostend or the 3′ most end of the probe or primer. In a specific preferredembodiment that is particularly suitable for use in a oligonucleotideligation assay (U.S. Pat. No. 4,988,617), the 3′most nucleotide of theprobe aligns with the SNP position in the target sequence.

Oligonucleotide probes and primers may be prepared by methods well knownin the art. Chemical synthetic methods include, but are not limited to,the phosphotriester method described by Narang et al., Methods inEnzymology 68:90 (1979); the phosphodiester method described by Brown etal., Methods in Enzymology 68:109 (1979); the diethylphosphoamidatemethod described by Beaucage et al., Tetrahedron Letters 22:1859 (1981);and the solid support method described in U.S. Pat. No. 4,458,066.

Allele-specific probes are often used in pairs (or, less commonly, insets of 3 or 4, such as if a SNP position is known to have 3 or 4alleles, respectively, or to assay both strands of a nucleic acidmolecule for a target SNP allele), and such pairs may be identicalexcept for a one nucleotide mismatch that represents the allelicvariants at the SNP position. Commonly, one member of a pair perfectlymatches a reference form of a target sequence that has a more common SNPallele (i.e., the allele that is more frequent in the target population)and the other member of the pair perfectly matches a form of the targetsequence that has a less common SNP allele (i.e., the allele that israrer in the target population). In the case of an array, multiple pairsof probes can be immobilized on the same support for simultaneousanalysis of multiple different polymorphisms.

In one type of PCR-based assay, an allele-specific primer hybridizes toa region on a target nucleic acid molecule that overlaps a SNP positionand only primes amplification of an allelic form to which the primerexhibits perfect complementarity. Gibbs, Nucleic Acid Res 17:2427-2448(1989). Typically, the primer's 3′-most nucleotide is aligned with andcomplementary to the SNP position of the target nucleic acid molecule.This primer is used in conjunction with a second primer that hybridizesat a distal site. Amplification proceeds from the two primers, producinga detectable product that indicates which allelic form is present in thetest sample. A control is usually performed with a second pair ofprimers, one of which shows a single base mismatch at the polymorphicsite and the other of which exhibits perfect complementarity to a distalsite. The single-base mismatch prevents amplification or substantiallyreduces amplification efficiency, so that either no detectable productis formed or it is formed in lower amounts or at a slower pace. Themethod generally works most effectively when the mismatch is at the3′-most position of the oligonucleotide (i.e., the 3′-most position ofthe oligonucleotide aligns with the target SNP position) because thisposition is most destabilizing to elongation from the primer (see, e.g.,WO 93/22456). This PCR-based assay can be utilized as part of the TaqManassay, described below.

In a specific embodiment of the invention, a primer of the inventioncontains a sequence substantially complementary to a segment of a targetSNP-containing nucleic acid molecule except that the primer has amismatched nucleotide in one of the three nucleotide positions at the3′-most end of the primer, such that the mismatched nucleotide does notbase pair with a particular allele at the SNP site. In a preferredembodiment, the mismatched nucleotide in the primer is the second fromthe last nucleotide at the 3′-most position of the primer. In a morepreferred embodiment, the mismatched nucleotide in the primer is thelast nucleotide at the 3′-most position of the primer.

In another embodiment of the invention, a SNP detection reagent of theinvention is labeled with a fluorogenic reporter dye that emits adetectable signal. While the preferred reporter dye is a fluorescentdye, any reporter dye that can be attached to a detection reagent suchas an oligonucleotide probe or primer is suitable for use in theinvention. Such dyes include, but are not limited to, Acridine, AMCA,BODIPY, Cascade Blue, Cy2, Cy3, Cy5, Cy7, Dabcyl, Edans, Eosin,Erythrosin, Fluorescein, 6-Fam, Tet, Joe, Hex, Oregon Green, Rhodamine,Rhodol Green, Tamra, Rox, and Texas Red.

In yet another embodiment of the invention, the detection reagent may befurther labeled with a quencher dye such as Tamra, especially when thereagent is used as a self-quenching probe such as a TaqMan (U.S. Pat.Nos. 5,210,015 and 5,538,848) or Molecular Beacon probe (U.S. Pat. Nos.5,118,801 and 5,312,728), or other stemless or linear beacon probe(Livak et al., PCR Method Appl 4:357-362 (1995); Tyagi et al., NatureBiotechnology 14:303-308 (1996); Nazarenko et al., Nucl Acids Res25:2516-2521 (1997); U.S. Pat. Nos. 5,866,336 and 6,117,635.

The detection reagents of the invention may also contain other labels,including but not limited to, biotin for streptavidin binding, haptenfor antibody binding, and oligonucleotide for binding to anothercomplementary oligonucleotide such as pairs of zipcodes.

The present invention also contemplates reagents that do not contain (orthat are complementary to) a SNP nucleotide identified herein but thatare used to assay one or more SNPs disclosed herein. For example,primers that flank, but do not hybridize directly to a target SNPposition provided herein are useful in primer extension reactions inwhich the primers hybridize to a region adjacent to the target SNPposition (i.e., within one or more nucleotides from the target SNPsite). During the primer extension reaction, a primer is typically notable to extend past a target SNP site if a particular nucleotide(allele) is present at that target SNP site, and the primer extensionproduct can be detected in order to determine which SNP allele ispresent at the target SNP site. For example, particular ddNTPs aretypically used in the primer extension reaction to terminate primerextension once a ddNTP is incorporated into the extension product (aprimer extension product which includes a ddNTP at the 3′-most end ofthe primer extension product, and in which the ddNTP is a nucleotide ofa SNP disclosed herein, is a composition that is specificallycontemplated by the present invention). Thus, reagents that bind to anucleic acid molecule in a region adjacent to a SNP site and that areused for assaying the SNP site, even though the bound sequences do notnecessarily include the SNP site itself, are also contemplated by thepresent invention.

SNP Detection Kits and Systems

A person skilled in the art will recognize that, based on the SNP andassociated sequence information disclosed herein, detection reagents canbe developed and used to assay any SNP of the present inventionindividually or in combination, and such detection reagents can bereadily incorporated into one of the established kit or system formatswhich are well known in the art. The terms “kits” and “systems,” as usedherein in the context of SNP detection reagents, are intended to referto such things as combinations of multiple SNP detection reagents, orone or more SNP detection reagents in combination with one or more othertypes of elements or components (e.g., other types of biochemicalreagents, containers, packages such as packaging intended for commercialsale, substrates to which SNP detection reagents are attached,electronic hardware components, etc.). Accordingly, the presentinvention further provides SNP detection kits and systems, including butnot limited to, packaged probe and primer sets (e.g. TaqMan probe/primersets), arrays/microarrays of nucleic acid molecules, and beads thatcontain one or more probes, primers, or other detection reagents fordetecting one or more SNPs of the present invention. The kits/systemscan optionally include various electronic hardware components; forexample, arrays (“DNA chips”) and microfluidic systems (“lab-on-a-chip”systems) provided by various manufacturers typically comprise hardwarecomponents. Other kits/systems (e.g., probe/primer sets) may not includeelectronic hardware components, but may be comprised of, for example,one or more SNP detection reagents (along with, optionally, otherbiochemical reagents) packaged in one or more containers.

In some embodiments, a SNP detection kit typically contains one or moredetection reagents and other components (e.g. a buffer, enzymes such asDNA polymerases or ligases, chain extension nucleotides such asdeoxynucleotide triphosphates, and in the case of Sanger-type DNAsequencing reactions, chain terminating nucleotides, positive controlsequences, negative control sequences, and the like) necessary to carryout an assay or reaction, such as amplification and/or detection of aSNP-containing nucleic acid molecule. A kit may further contain meansfor determining the amount of a target nucleic acid, and means forcomparing the amount with a standard, and can comprise instructions forusing the kit to detect the SNP-containing nucleic acid molecule ofinterest. In one embodiment of the present invention, kits are providedwhich contain the necessary reagents to carry out one or more assays todetect one or more SNPs disclosed herein. In a preferred embodiment ofthe present invention, SNP detection kits/systems are in the form ofnucleic acid arrays, or compartmentalized kits, includingmicrofluidic/lab-on-a-chip systems.

SNP detection kits/systems may contain, for example, one or more probes,or pairs of probes, that hybridize to a nucleic acid molecule at or neareach target SNP position. Multiple pairs of allele-specific probes maybe included in the kit/system to simultaneously assay large numbers ofSNPs, at least one of which is a SNP of the present invention. In somekits/systems, the allele-specific probes are immobilized to a substratesuch as an array or bead. For example, the same substrate can compriseallele-specific probes for detecting at least 1; 10; 100; 1000; 10,000;100,000 (or any other number in-between) or substantially all of theSNPs shown in Table 1 and/or Table 2.

The terms “arrays,” “microarrays,” and “DNA chips” are used hereininterchangeably to refer to an array of distinct polynucleotides affixedto a substrate, such as glass, plastic, paper, nylon or other type ofmembrane, filter, chip, or any other suitable solid support. Thepolynucleotides can be synthesized directly on the substrate, orsynthesized separate from the substrate and then affixed to thesubstrate. In one embodiment, the microarray is prepared and usedaccording to the methods described in Chee et al., U.S. Pat. No.5,837,832 and PCT application WO95/11995; D. J. Lockhart et al., NatBiotech 14:1675-1680 (1996); and M. Schena et al., Proc Natl Acad Sci93:10614-10619 (1996), all of which are incorporated herein in theirentirety by reference. In other embodiments, such arrays are produced bythe methods described by Brown et al., U.S. Pat. No. 5,807,522.

Nucleic acid arrays are reviewed in the following references: Zammatteoet al., “New chips for molecular biology and diagnostics,” BiotechnolAnnu Rev 8:85-101 (2002); Sosnowski et al., “Active microelectronicarray system for DNA hybridization, genotyping and pharmacogenomicapplications,” Psychiatr Genet 12(4):181-92 (December 2002); Heller,“DNA microarray technology: devices, systems, and applications,” AnnuRev Biomed Eng 4:129-53 (2002); Epub Mar. 22, 2002; Kolchinsky et al.,“Analysis of SNPs and other genomic variations using gel-based chips,”Hum Mutat 19(4):343-60 (April 2002); and McGall et al., “High-densitygenechip oligonucleotide probe arrays,” Adv Biochem Eng Biotechnol77:21-42 (2002).

Any number of probes, such as allele-specific probes, may be implementedin an array, and each probe or pair of probes can hybridize to adifferent SNP position. In the case of polynucleotide probes, they canbe synthesized at designated areas (or synthesized separately and thenaffixed to designated areas) on a substrate using a light-directedchemical process. Each DNA chip can contain, for example, thousands tomillions of individual synthetic polynucleotide probes arranged in agrid-like pattern and miniaturized (e.g., to the size of a dime).Preferably, probes are attached to a solid support in an ordered,addressable array.

A microarray can be composed of a large number of unique,single-stranded polynucleotides, usually either synthetic antisensepolynucleotides or fragments of cDNAs, fixed to a solid support. Typicalpolynucleotides are preferably about 6-60 nucleotides in length, morepreferably about 15-30 nucleotides in length, and most preferably about18-25 nucleotides in length. For certain types of microarrays or otherdetection kits/systems, it may be preferable to use oligonucleotidesthat are only about 7-20 nucleotides in length. In other types ofarrays, such as arrays used in conjunction with chemiluminescentdetection technology, preferred probe lengths can be, for example, about15-80 nucleotides in length, preferably about 50-70 nucleotides inlength, more preferably about 55-65 nucleotides in length, and mostpreferably about 60 nucleotides in length. The microarray or detectionkit can contain polynucleotides that cover the known 5′ or 3′ sequenceof a gene/transcript or target SNP site, sequential polynucleotides thatcover the full-length sequence of a gene/transcript; or uniquepolynucleotides selected from particular areas along the length of atarget gene/transcript sequence, particularly areas corresponding to oneor more SNPs disclosed in Table 1 and/or Table 2. Polynucleotides usedin the microarray or detection kit can be specific to a SNP or SNPs ofinterest (e.g., specific to a particular SNP allele at a target SNPsite, or specific to particular SNP alleles at multiple different SNPsites), or specific to a polymorphic gene/transcript orgenes/transcripts of interest.

Hybridization assays based on polynucleotide arrays rely on thedifferences in hybridization stability of the probes to perfectlymatched and mismatched target sequence variants. For SNP genotyping, itis generally preferable that stringency conditions used in hybridizationassays are high enough such that nucleic acid molecules that differ fromone another at as little as a single SNP position can be differentiated(e.g., typical SNP hybridization assays are designed so thathybridization will occur only if one particular nucleotide is present ata SNP position, but will not occur if an alternative nucleotide ispresent at that SNP position). Such high stringency conditions may bepreferable when using, for example, nucleic acid arrays ofallele-specific probes for SNP detection. Such high stringencyconditions are described in the preceding section, and are well known tothose skilled in the art and can be found in, for example, CurrentProtocols in Molecular Biology 6.3.1-6.3.6, John Wiley & Sons, N.Y.(1989).

In other embodiments, the arrays are used in conjunction withchemiluminescent detection technology. The following patents and patentapplications, which are all hereby incorporated by reference, provideadditional information pertaining to chemiluminescent detection. U.S.patent applications that describe chemiluminescent approaches formicroarray detection: Ser. Nos. 10/620,332 and 10/620333. U.S. patentsthat describe methods and compositions of dioxetane for performingchemiluminescent detection: U.S. Pat. Nos. 6,124,478; 6,107,024;5,994,073; 5,981,768; 5,871,938; 5,843,681; 5,800,999 and 5,773,628. Andthe U.S. published application that discloses methods and compositionsfor microarray controls: US2002/0110828.

In one embodiment of the invention, a nucleic acid array can comprise anarray of probes of about 15-25 nucleotides in length. In furtherembodiments, a nucleic acid array can comprise any number of probes, inwhich at least one probe is capable of detecting one or more SNPsdisclosed in Table 1 and/or Table 2, and/or at least one probe comprisesa fragment of one of the sequences selected from the group consisting ofthose disclosed in Table 1, Table 2, the Sequence Listing, and sequencescomplementary thereto, said fragment comprising at least about 8consecutive nucleotides, preferably 10, 12, 15, 16, 18, 20, morepreferably 22, 25, 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100, or moreconsecutive nucleotides (or any other number in-between) and containing(or being complementary to) a novel SNP allele disclosed in Table 1and/or Table 2. In some embodiments, the nucleotide complementary to theSNP site is within 5, 4, 3, 2, or 1 nucleotide from the center of theprobe, more preferably at the center of said probe.

A polynucleotide probe can be synthesized on the surface of thesubstrate by using a chemical coupling procedure and an ink jetapplication apparatus, as described in PCT application WO95/251116(Baldeschweiler et al.) which is incorporated herein in its entirety byreference. In another aspect, a “gridded” array analogous to a dot (orslot) blot may be used to arrange and link cDNA fragments oroligonucleotides to the surface of a substrate using a vacuum system,thermal, UV, mechanical or chemical bonding procedures. An array, suchas those described above, may be produced by hand or by using availabledevices (slot blot or dot blot apparatus), materials (any suitable solidsupport), and machines (including robotic instruments), and may contain8, 24, 96, 384, 1536, 6144 or more polynucleotides, or any other numberwhich lends itself to the efficient use of commercially availableinstrumentation.

Using such arrays or other kits/systems, the present invention providesmethods of identifying the SNPs disclosed herein in a test sample. Suchmethods typically involve incubating a test sample of nucleic acids withan array comprising one or more probes corresponding to at least one SNPposition of the present invention, and assaying for binding of a nucleicacid from the test sample with one or more of the probes. Conditions forincubating a SNP detection reagent (or a kit/system that employs one ormore such SNP detection reagents) with a test sample vary. Incubationconditions depend on such factors as the format employed in the assay,the detection methods employed, and the type and nature of the detectionreagents used in the assay. One skilled in the art will recognize thatany one of the commonly available hybridization, amplification and arrayassay formats can readily be adapted to detect the SNPs disclosedherein.

A SNP detection kit/system of the present invention may includecomponents that are used to prepare nucleic acids from a test sample forthe subsequent amplification and/or detection of a SNP-containingnucleic acid molecule. Such sample preparation components can be used toproduce nucleic acid extracts (including DNA and/or RNA), proteins ormembrane extracts from any bodily fluids (such as blood, serum, plasma,urine, saliva, phlegm, gastric juices, semen, tears, sweat, etc.), skin,hair, cells (especially nucleated cells), biopsies, buccal swabs ortissue specimens. The test samples used in the above-described methodswill vary based on such factors as the assay format, nature of thedetection method, and the specific tissues, cells or extracts used asthe test sample to be assayed. Methods of preparing nucleic acids,proteins, and cell extracts are well known in the art and can be readilyadapted to obtain a sample that is compatible with the system utilized.Automated sample preparation systems for extracting nucleic acids from atest sample are commercially available, and examples are Qiagen'sBioRobot 9600, Applied Biosystems' PRISM™ 6700 sample preparationsystem, and Roche Molecular Systems' COBAS AmpliPrep System.

Another form of kit contemplated by the present invention is acompartmentalized kit. A compartmentalized kit includes any kit in whichreagents are contained in separate containers. Such containers include,for example, small glass containers, plastic containers, strips ofplastic, glass or paper, or arraying material such as silica. Suchcontainers allow one to efficiently transfer reagents from onecompartment to another compartment such that the test samples andreagents are not cross-contaminated, or from one container to anothervessel not included in the kit, and the agents or solutions of eachcontainer can be added in a quantitative fashion from one compartment toanother or to another vessel. Such containers may include, for example,one or more containers which will accept the test sample, one or morecontainers which contain at least one probe or other SNP detectionreagent for detecting one or more SNPs of the present invention, one ormore containers which contain wash reagents (such as phosphate bufferedsaline, Tris-buffers, etc.), and one or more containers which containthe reagents used to reveal the presence of the bound probe or other SNPdetection reagents. The kit can optionally further comprise compartmentsand/or reagents for, for example, nucleic acid amplification or otherenzymatic reactions such as primer extension reactions, hybridization,ligation, electrophoresis (preferably capillary electrophoresis), massspectrometry, and/or laser-induced fluorescent detection. The kit mayalso include instructions for using the kit. Exemplary compartmentalizedkits include microfluidic devices known in the art. See, e.g., Weigl etal., “Lab-on-a-chip for drug development,” Adv Drug Deliv Rev55(3):349-77 (February 2003). In such microfluidic devices, thecontainers may be referred to as, for example, microfluidic“compartments,” “chambers,” or “channels.”

Microfluidic devices, which may also be referred to as “lab-on-a-chip”systems, biomedical micro-electro-mechanical systems (bioMEMs), ormulticomponent integrated systems, are exemplary kits/systems of thepresent invention for analyzing SNPs. Such systems miniaturize andcompartmentalize processes such as probe/target hybridization, nucleicacid amplification, and capillary electrophoresis reactions in a singlefunctional device. Such microfluidic devices typically utilize detectionreagents in at least one aspect of the system, and such detectionreagents may be used to detect one or more SNPs of the presentinvention. One example of a microfluidic system is disclosed in U.S.Pat. No. 5,589,136, which describes the integration of PCR amplificationand capillary electrophoresis in chips. Exemplary microfluidic systemscomprise a pattern of microchannels designed onto a glass, silicon,quartz, or plastic wafer included on a microchip. The movements of thesamples may be controlled by electric, electroosmotic or hydrostaticforces applied across different areas of the microchip to createfunctional microscopic valves and pumps with no moving parts. Varyingthe voltage can be used as a means to control the liquid flow atintersections between the micro-machined channels and to change theliquid flow rate for pumping across different sections of the microchip.See, for example, U.S. Pat. No. 6,153,073, Dubrow et al., and U.S. Pat.No. 6,156,181, Parce et al.

For genotyping SNPs, an exemplary microfluidic system may integrate, forexample, nucleic acid amplification, primer extension, capillaryelectrophoresis, and a detection method such as laser inducedfluorescence detection. In a first step of an exemplary process forusing such an exemplary system, nucleic acid samples are amplified,preferably by PCR. Then, the amplification products are subjected toautomated primer extension reactions using ddNTPs (specific fluorescencefor each ddNTP) and the appropriate oligonucleotide primers to carry outprimer extension reactions which hybridize just upstream of the targetedSNP. Once the extension at the 3′ end is completed, the primers areseparated from the unincorporated fluorescent ddNTPs by capillaryelectrophoresis. The separation medium used in capillary electrophoresiscan be, for example, polyacrylamide, polyethyleneglycol or dextran. Theincorporated ddNTPs in the single nucleotide primer extension productsare identified by laser-induced fluorescence detection. Such anexemplary microchip can be used to process, for example, at least 96 to384 samples, or more, in parallel.

Uses of Nucleic Acid Molecules

The nucleic acid molecules of the present invention have a variety ofuses, especially for the diagnosis, prognosis, treatment, and preventionof CHD (particularly MI) and aneurysm/dissection, and for predictingdrug response, particularly response to statins. For example, thenucleic acid molecules of the invention are useful for predicting anindividual's risk for developing CHD (particularly the risk forexperiencing a first or recurrent MI) or aneurysm/dissection, forprognosing the progression of CHD (e.g., the severity or consequences ofMI) or aneurysm/dissection in an individual, in evaluating thelikelihood of an individual who has CHD or aneurysm/dissection (or whois at increased risk for CHD or aneurysm/dissection) of responding totreatment (or prevention) of CHD or aneurysm/dissection with statin,and/or predicting the likelihood that the individual will experiencetoxicity or other undesirable side effects from the statin treatment,etc. For example, the nucleic acid molecules are useful as hybridizationprobes, such as for genotyping SNPs in messenger RNA, transcript, cDNA,genomic DNA, amplified DNA or other nucleic acid molecules, and forisolating full-length cDNA and genomic clones encoding the variantpeptides disclosed in Table 1 as well as their orthologs.

A probe can hybridize to any nucleotide sequence along the entire lengthof a nucleic acid molecule referred to in Table 1 and/or Table 2.Preferably, a probe of the present invention hybridizes to a region of atarget sequence that encompasses a SNP position indicated in Table 1and/or Table 2. More preferably, a probe hybridizes to a SNP-containingtarget sequence in a sequence-specific manner such that it distinguishesthe target sequence from other nucleotide sequences which vary from thetarget sequence only by which nucleotide is present at the SNP site.Such a probe is particularly useful for detecting the presence of aSNP-containing nucleic acid in a test sample, or for determining whichnucleotide (allele) is present at a particular SNP site (i.e.,genotyping the SNP site).

A nucleic acid hybridization probe may be used for determining thepresence, level, form, and/or distribution of nucleic acid expression.The nucleic acid whose level is determined can be DNA or RNA.Accordingly, probes specific for the SNPs described herein can be usedto assess the presence, expression and/or gene copy number in a givencell, tissue, or organism. These uses are relevant for diagnosis ofdisorders involving an increase or decrease in gene expression relativeto normal levels. In vitro techniques for detection of mRNA include, forexample, Northern blot hybridizations and in situ hybridizations. Invitro techniques for detecting DNA include Southern blot hybridizationsand in situ hybridizations. Sambrook and Russell, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Press, N.Y. (2000).

Probes can be used as part of a diagnostic test kit for identifyingcells or tissues in which a variant protein is expressed, such as bymeasuring the level of a variant protein-encoding nucleic acid (e.g.,mRNA) in a sample of cells from a subject or determining if apolynucleotide contains a SNP of interest.

Thus, the nucleic acid molecules of the invention can be used ashybridization probes to detect the SNPs disclosed herein, therebydetermining whether an individual with the polymorphism(s) is at riskfor developing CHD or aneurysm/dissection (or has already developedearly stage CHD or aneurysm/dissection), or the likelihood that anindividual will respond positively to statin treatment (includingpreventive treatment) of CHD or aneurysm/dissection. Detection of a SNPassociated with a disease phenotype provides a diagnostic tool for anactive disease and/or genetic predisposition to the disease.

Furthermore, the nucleic acid molecules of the invention are thereforeuseful for detecting a gene (gene information is disclosed in Table 2,for example) which contains a SNP disclosed herein and/or products ofsuch genes, such as expressed mRNA transcript molecules (transcriptinformation is disclosed in Table 1, for example), and are thus usefulfor detecting gene expression. The nucleic acid molecules can optionallybe implemented in, for example, an array or kit format for use indetecting gene expression.

The nucleic acid molecules of the invention are also useful as primersto amplify any given region of a nucleic acid molecule, particularly aregion containing a SNP identified in Table 1 and/or Table 2.

The nucleic acid molecules of the invention are also useful forconstructing recombinant vectors (described in greater detail below).Such vectors include expression vectors that express a portion of, orall of, any of the variant peptide sequences referred to in Table 1.Vectors also include insertion vectors, used to integrate into anothernucleic acid molecule sequence, such as into the cellular genome, toalter in situ expression of a gene and/or gene product. For example, anendogenous coding sequence can be replaced via homologous recombinationwith all or part of the coding region containing one or morespecifically introduced SNPs.

The nucleic acid molecules of the invention are also useful forexpressing antigenic portions of the variant proteins, particularlyantigenic portions that contain a variant amino acid sequence (e.g., anamino acid substitution) caused by a SNP disclosed in Table 1 and/orTable 2. The nucleic acid molecules of the invention are also useful forconstructing vectors containing a gene regulatory region of the nucleicacid molecules of the present invention.

The nucleic acid molecules of the invention are also useful fordesigning ribozymes corresponding to all, or a part, of an mRNA moleculeexpressed from a SNP-containing nucleic acid molecule described herein.

The nucleic acid molecules of the invention are also useful forconstructing host cells expressing a part, or all, of the nucleic acidmolecules and variant peptides.

The nucleic acid molecules of the invention are also useful forconstructing transgenic animals expressing all, or a part, of thenucleic acid molecules and variant peptides. The production ofrecombinant cells and transgenic animals having nucleic acid moleculeswhich contain the SNPs disclosed in Table 1 and/or Table 2 allows, forexample, effective clinical design of treatment compounds and dosageregimens.

The nucleic acid molecules of the invention are also useful in assaysfor drug screening to identify compounds that, for example, modulatenucleic acid expression.

The nucleic acid molecules of the invention are also useful in genetherapy in patients whose cells have aberrant gene expression. Thus,recombinant cells, which include a patient's cells that have beenengineered ex vivo and returned to the patient, can be introduced intoan individual where the recombinant cells produce the desired protein totreat the individual.

SNP Genotyping Methods

The process of determining which specific nucleotide (i.e., allele) ispresent at each of one or more SNP positions, such as a SNP position ina nucleic acid molecule disclosed in Table 1 and/or Table 2, is referredto as SNP genotyping. The present invention provides methods of SNPgenotyping, such as for use in evaluating an individual's risk fordeveloping CHD (particularly MI) or aneurysm/dissection, for evaluatingan individual's prognosis for disease severity and recovery, forpredicting the likelihood that an individual who has previously had CHD(e.g., MI) or aneurysm/dissection will have CHD or aneurysm/dissectionagain in the future (e.g., one or more recurrent MI's oraneurysms/dissections), for implementing a preventive or treatmentregimen for an individual based on that individual having an increasedsusceptibility for developing CHD (e.g., increased risk for MI) oraneurysm/dissection, in evaluating an individual's likelihood ofresponding to statin treatment (particularly for treating or preventingCHD or aneurysm/dissection), in selecting a treatment or preventiveregimen (e.g., in deciding whether or not to administer statin treatmentto an individual having CHD or aneurysm/dissection, or who is atincreased risk for developing CHD or aneurysm/dissection in the future),or in formulating or selecting a particular statin-based treatment orpreventive regimen such as dosage and/or frequency of administration ofstatin treatment or choosing which form/type of statin to beadministered, such as a particular pharmaceutical composition orcompound, etc.), determining the likelihood of experiencing toxicity orother undesirable side effects from statin treatment, or selectingindividuals for a clinical trial of a statin (e.g., selectingindividuals to participate in the trial who are most likely to respondpositively from the statin treatment, and/or excluding individuals fromthe trial who are unlikely to respond positively from the statintreatment), etc.

Nucleic acid samples can be genotyped to determine which allele(s)is/are present at any given genetic region (e.g., SNP position) ofinterest by methods well known in the art. The neighboring sequence canbe used to design SNP detection reagents such as oligonucleotide probes,which may optionally be implemented in a kit format. Exemplary SNPgenotyping methods are described in Chen et al., “Single nucleotidepolymorphism genotyping: biochemistry, protocol, cost and throughput,”Pharmacogenomics J 3(2):77-96 (2003); Kwok et al., “Detection of singlenucleotide polymorphisms,” Curr Issues Mol Biol 5(2):43-60 (April 2003);Shi, “Technologies for individual genotyping: detection of geneticpolymorphisms in drug targets and disease genes,” Am J Pharmacogenomics2(3):197-205 (2002); and Kwok, “Methods for genotyping single nucleotidepolymorphisms,” Annu Rev Genomics Hum Genet 2:235-58 (2001). Exemplarytechniques for high-throughput SNP genotyping are described inMarnellos, “High-throughput SNP analysis for genetic associationstudies,” Curr Opin Drug Discov Devel 6(3):317-21 (May 2003). Common SNPgenotyping methods include, but are not limited to, TaqMan assays,molecular beacon assays, nucleic acid arrays, allele-specific primerextension, allele-specific PCR, arrayed primer extension, homogeneousprimer extension assays, primer extension with detection by massspectrometry, pyrosequencing, multiplex primer extension sorted ongenetic arrays, ligation with rolling circle amplification, homogeneousligation, OLA (U.S. Pat. No. 4,988,167), multiplex ligation reactionsorted on genetic arrays, restriction-fragment length polymorphism,single base extension-tag assays, and the Invader assay. Such methodsmay be used in combination with detection mechanisms such as, forexample, luminescence or chemiluminescence detection, fluorescencedetection, time-resolved fluorescence detection, fluorescence resonanceenergy transfer, fluorescence polarization, mass spectrometry, andelectrical detection.

Various methods for detecting polymorphisms include, but are not limitedto, methods in which protection from cleavage agents is used to detectmismatched bases in RNA/RNA or RNA/DNA duplexes (Myers et al., Science230:1242 (1985); Cotton et al., PNAS 85:4397 (1988); and Saleeba et al.,Meth. Enzymol 217:286-295 (1992)), comparison of the electrophoreticmobility of variant and wild type nucleic acid molecules (Orita et al.,PNAS 86:2766 (1989); Cotton et al., Mutat Res 285:125-144 (1993); andHayashi et al., Genet Anal Tech Appl 9:73-79 (1992)), and assaying themovement of polymorphic or wild-type fragments in polyacrylamide gelscontaining a gradient of denaturant using denaturing gradient gelelectrophoresis (DGGE) (Myers et al., Nature 313:495 (1985)). Sequencevariations at specific locations can also be assessed by nucleaseprotection assays such as RNase and S1 protection or chemical cleavagemethods.

In a preferred embodiment, SNP genotyping is performed using the TaqManassay, which is also known as the 5′ nuclease assay (U.S. Pat. Nos.5,210,015 and 5,538,848). The TaqMan assay detects the accumulation of aspecific amplified product during PCR. The TaqMan assay utilizes anoligonucleotide probe labeled with a fluorescent reporter dye and aquencher dye. The reporter dye is excited by irradiation at anappropriate wavelength, it transfers energy to the quencher dye in thesame probe via a process called fluorescence resonance energy transfer(FRET). When attached to the probe, the excited reporter dye does notemit a signal. The proximity of the quencher dye to the reporter dye inthe intact probe maintains a reduced fluorescence for the reporter. Thereporter dye and quencher dye may be at the 5′ most and the 3′ mostends, respectively, or vice versa. Alternatively, the reporter dye maybe at the 5′ or 3′ most end while the quencher dye is attached to aninternal nucleotide, or vice versa. In yet another embodiment, both thereporter and the quencher may be attached to internal nucleotides at adistance from each other such that fluorescence of the reporter isreduced.

During PCR, the 5′ nuclease activity of DNA polymerase cleaves theprobe, thereby separating the reporter dye and the quencher dye andresulting in increased fluorescence of the reporter. Accumulation of PCRproduct is detected directly by monitoring the increase in fluorescenceof the reporter dye. The DNA polymerase cleaves the probe between thereporter dye and the quencher dye only if the probe hybridizes to thetarget SNP-containing template which is amplified during PCR, and theprobe is designed to hybridize to the target SNP site only if aparticular SNP allele is present.

Preferred TaqMan primer and probe sequences can readily be determinedusing the SNP and associated nucleic acid sequence information providedherein. A number of computer programs, such as Primer Express (AppliedBiosystems, Foster City, Calif.), can be used to rapidly obtain optimalprimer/probe sets. It will be apparent to one of skill in the art thatsuch primers and probes for detecting the SNPs of the present inventionare useful in, for example, screening for individuals who aresusceptible to developing CHD (particularly MI), aneurysm/dissection,and related pathologies, or in screening individuals who have CHD oraneurysm/dissection (or who are susceptible to CHD oraneurysm/dissection) for their likelihood of responding to statintreatment. These probes and primers can be readily incorporated into akit format. The present invention also includes modifications of theTaqman assay well known in the art such as the use of Molecular Beaconprobes (U.S. Pat. Nos. 5,118,801 and 5,312,728) and other variantformats (U.S. Pat. Nos. 5,866,336 and 6,117,635).

Another preferred method for genotyping the SNPs of the presentinvention is the use of two oligonucleotide probes in an OLA (see, e.g.,U.S. Pat. No. 4,988,617). In this method, one probe hybridizes to asegment of a target nucleic acid with its 3′ most end aligned with theSNP site. A second probe hybridizes to an adjacent segment of the targetnucleic acid molecule directly 3′ to the first probe. The two juxtaposedprobes hybridize to the target nucleic acid molecule, and are ligated inthe presence of a linking agent such as a ligase if there is perfectcomplementarity between the 3′ most nucleotide of the first probe withthe SNP site. If there is a mismatch, ligation would not occur. Afterthe reaction, the ligated probes are separated from the target nucleicacid molecule, and detected as indicators of the presence of a SNP.

The following patents, patent applications, and published internationalpatent applications, which are all hereby incorporated by reference,provide additional information pertaining to techniques for carrying outvarious types of OLA. The following U.S. patents describe OLA strategiesfor performing SNP detection: U.S. Pat. Nos. 6,027,889; 6,268,148;5,494,810; 5,830,711 and 6,054,564. WO 97/31256 and WO 00/56927 describeOLA strategies for performing SNP detection using universal arrays,wherein a zipcode sequence can be introduced into one of thehybridization probes, and the resulting product, or amplified product,hybridized to a universal zip code array. U.S. application US01/17329(and 09/584,905) describes OLA (or LDR) followed by PCR, whereinzipcodes are incorporated into OLA probes, and amplified PCR productsare determined by electrophoretic or universal zipcode array readout.U.S. applications 60/427,818, 60/445636, and 60/445494 describe SNPlexmethods and software for multiplexed SNP detection using OLA followed byPCR, wherein zipcodes are incorporated into OLA probes, and amplifiedPCR products are hybridized with a zipchute reagent, and the identity ofthe SNP determined from electrophoretic readout of the zipchute. In someembodiments, OLA is carried out prior to PCR (or another method ofnucleic acid amplification). In other embodiments, PCR (or anothermethod of nucleic acid amplification) is carried out prior to OLA.

Another method for SNP genotyping is based on mass spectrometry. Massspectrometry takes advantage of the unique mass of each of the fournucleotides of DNA. SNPs can be unambiguously genotyped by massspectrometry by measuring the differences in the mass of nucleic acidshaving alternative SNP alleles. MALDI-TOF (Matrix Assisted LaserDesorption Ionization—Time of Flight) mass spectrometry technology ispreferred for extremely precise determinations of molecular mass, suchas SNPs. Numerous approaches to SNP analysis have been developed basedon mass spectrometry. Preferred mass spectrometry-based methods of SNPgenotyping include primer extension assays, which can also be utilizedin combination with other approaches, such as traditional gel-basedformats and microarrays.

Typically, the primer extension assay involves designing and annealing aprimer to a template PCR amplicon upstream (5′) from a target SNPposition. A mix of dideoxynucleotide triphosphates (ddNTPs) and/ordeoxynucleotide triphosphates (dNTPs) are added to a reaction mixturecontaining template (e.g., a SNP-containing nucleic acid molecule whichhas typically been amplified, such as by PCR), primer, and DNApolymerase. Extension of the primer terminates at the first position inthe template where a nucleotide complementary to one of the ddNTPs inthe mix occurs. The primer can be either immediately adjacent (i.e., thenucleotide at the 3′ end of the primer hybridizes to the nucleotide nextto the target SNP site) or two or more nucleotides removed from the SNPposition. If the primer is several nucleotides removed from the targetSNP position, the only limitation is that the template sequence betweenthe 3′ end of the primer and the SNP position cannot contain anucleotide of the same type as the one to be detected, or this willcause premature termination of the extension primer. Alternatively, ifall four ddNTPs alone, with no dNTPs, are added to the reaction mixture,the primer will always be extended by only one nucleotide, correspondingto the target SNP position. In this instance, primers are designed tobind one nucleotide upstream from the SNP position (i.e., the nucleotideat the 3′ end of the primer hybridizes to the nucleotide that isimmediately adjacent to the target SNP site on the 5′ side of the targetSNP site). Extension by only one nucleotide is preferable, as itminimizes the overall mass of the extended primer, thereby increasingthe resolution of mass differences between alternative SNP nucleotides.Furthermore, mass-tagged ddNTPs can be employed in the primer extensionreactions in place of unmodified ddNTPs. This increases the massdifference between primers extended with these ddNTPs, thereby providingincreased sensitivity and accuracy, and is particularly useful fortyping heterozygous base positions. Mass-tagging also alleviates theneed for intensive sample-preparation procedures and decreases thenecessary resolving power of the mass spectrometer.

The extended primers can then be purified and analyzed by MALDI-TOF massspectrometry to determine the identity of the nucleotide present at thetarget SNP position. In one method of analysis, the products from theprimer extension reaction are combined with light absorbing crystalsthat form a matrix. The matrix is then hit with an energy source such asa laser to ionize and desorb the nucleic acid molecules into thegas-phase. The ionized molecules are then ejected into a flight tube andaccelerated down the tube towards a detector. The time between theionization event, such as a laser pulse, and collision of the moleculewith the detector is the time of flight of that molecule. The time offlight is precisely correlated with the mass-to-charge ratio (m/z) ofthe ionized molecule. Ions with smaller m/z travel down the tube fasterthan ions with larger m/z and therefore the lighter ions reach thedetector before the heavier ions. The time-of-flight is then convertedinto a corresponding, and highly precise, m/z. In this manner, SNPs canbe identified based on the slight differences in mass, and thecorresponding time of flight differences, inherent in nucleic acidmolecules having different nucleotides at a single base position. Forfurther information regarding the use of primer extension assays inconjunction with MALDI-TOF mass spectrometry for SNP genotyping, see,e.g., Wise et al., “A standard protocol for single nucleotide primerextension in the human genome using matrix-assisted laserdesorption/ionization time-of-flight mass spectrometry,” Rapid CommunMass Spectrom 17(11):1195-202 (2003).

The following references provide further information describing massspectrometry-based methods for SNP genotyping: Bocker, “SNP and mutationdiscovery using base-specific cleavage and MALDI-TOF mass spectrometry,”Bioinformatics 19 Suppl 1:144-153 (July 2003); Storm et al., “MALDI-TOFmass spectrometry-based SNP genotyping,” Methods Mol Biol 212:241-62(2003); Jurinke et al., “The use of Mass ARRAY technology for highthroughput genotyping,” Adv Biochem Eng Biotechnol 77:57-74 (2002); andJurinke et al., “Automated genotyping using the DNA MassArraytechnology,” Methods Mol Biol 187:179-92 (2002).

SNPs can also be scored by direct DNA sequencing. A variety of automatedsequencing procedures can be utilized (e.g. Biotechniques 19:448(1995)), including sequencing by mass spectrometry. See, e.g., PCTInternational Publication No. WO 94/16101; Cohen et al., Adv Chromatogr36:127-162 (1996); and Griffin et al., Appl Biochem Biotechnol38:147-159 (1993). The nucleic acid sequences of the present inventionenable one of ordinary skill in the art to readily design sequencingprimers for such automated sequencing procedures. Commercialinstrumentation, such as the Applied Biosystems 377, 3100, 3700, 3730,and 3730×1 DNA Analyzers (Foster City, Calif.), is commonly used in theart for automated sequencing.

Other methods that can be used to genotype the SNPs of the presentinvention include single-strand conformational polymorphism (SSCP), anddenaturing gradient gel electrophoresis (DGGE). Myers et al., Nature313:495 (1985). SSCP identifies base differences by alteration inelectrophoretic migration of single stranded PCR products, as describedin Orita et al., Proc. Nat. Acad. Single-stranded PCR products can begenerated by heating or otherwise denaturing double stranded PCRproducts. Single-stranded nucleic acids may refold or form secondarystructures that are partially dependent on the base sequence. Thedifferent electrophoretic mobilities of single-stranded amplificationproducts are related to base-sequence differences at SNP positions. DGGEdifferentiates SNP alleles based on the different sequence-dependentstabilities and melting properties inherent in polymorphic DNA and thecorresponding differences in electrophoretic migration patterns in adenaturing gradient gel. PCR Technology: Principles and Applications forDNA Amplification Chapter 7, Erlich, ed., W.H. Freeman and Co, N.Y.(1992).

Sequence-specific ribozymes (U.S. Pat. No. 5,498,531) can also be usedto score SNPs based on the development or loss of a ribozyme cleavagesite. Perfectly matched sequences can be distinguished from mismatchedsequences by nuclease cleavage digestion assays or by differences inmelting temperature. If the SNP affects a restriction enzyme cleavagesite, the SNP can be identified by alterations in restriction enzymedigestion patterns, and the corresponding changes in nucleic acidfragment lengths determined by gel electrophoresis.

SNP genotyping can include the steps of, for example, collecting abiological sample from a human subject (e.g., sample of tissues, cells,fluids, secretions, etc.), isolating nucleic acids (e.g., genomic DNA,mRNA or both) from the cells of the sample, contacting the nucleic acidswith one or more primers which specifically hybridize to a region of theisolated nucleic acid containing a target SNP under conditions such thathybridization and amplification of the target nucleic acid regionoccurs, and determining the nucleotide present at the SNP position ofinterest, or, in some assays, detecting the presence or absence of anamplification product (assays can be designed so that hybridizationand/or amplification will only occur if a particular SNP allele ispresent or absent). In some assays, the size of the amplificationproduct is detected and compared to the length of a control sample; forexample, deletions and insertions can be detected by a change in size ofthe amplified product compared to a normal genotype.

SNP genotyping is useful for numerous practical applications, asdescribed below. Examples of such applications include, but are notlimited to, SNP-disease association analysis, disease predispositionscreening, disease diagnosis, disease prognosis, disease progressionmonitoring, determining therapeutic strategies based on an individual'sgenotype (“pharmacogenomics”), developing therapeutic agents based onSNP genotypes associated with a disease or likelihood of responding to adrug, stratifying a patient population for clinical trial for atreatment regimen, predicting the likelihood that an individual willexperience toxic side effects from a therapeutic agent, and humanidentification applications such as forensics.

Analysis of Genetic Association Between SNPs and Phenotypic Traits

SNP genotyping for disease diagnosis, disease predisposition screening,disease prognosis, determining drug responsiveness (pharmacogenomics),drug toxicity screening, and other uses described herein, typicallyrelies on initially establishing a genetic association between one ormore specific SNPs and the particular phenotypic traits of interest.

Different study designs may be used for genetic association studies.Modern Epidemiology 609-622, Lippincott, Williams & Wilkins (1998).Observational studies are most frequently carried out in which theresponse of the patients is not interfered with. The first type ofobservational study identifies a sample of persons in whom the suspectedcause of the disease is present and another sample of persons in whomthe suspected cause is absent, and then the frequency of development ofdisease in the two samples is compared. These sampled populations arecalled cohorts, and the study is a prospective study. The other type ofobservational study is case-control or a retrospective study. In typicalcase-control studies, samples are collected from individuals with thephenotype of interest (cases) such as certain manifestations of adisease, and from individuals without the phenotype (controls) in apopulation (target population) that conclusions are to be drawn from.Then the possible causes of the disease are investigatedretrospectively. As the time and costs of collecting samples incase-control studies are considerably less than those for prospectivestudies, case-control studies are the more commonly used study design ingenetic association studies, at least during the exploration anddiscovery stage.

In both types of observational studies, there may be potentialconfounding factors that should be taken into consideration. Confoundingfactors are those that are associated with both the real cause(s) of thedisease and the disease itself, and they include demographic informationsuch as age, gender, ethnicity as well as environmental factors. Whenconfounding factors are not matched in cases and controls in a study,and are not controlled properly, spurious association results can arise.If potential confounding factors are identified, they should becontrolled for by analysis methods explained below.

In a genetic association study, the cause of interest to be tested is acertain allele or a SNP or a combination of alleles or a haplotype fromseveral SNPs. Thus, tissue specimens (e.g., whole blood) from thesampled individuals may be collected and genomic DNA genotyped for theSNP(s) of interest. In addition to the phenotypic trait of interest,other information such as demographic (e.g., age, gender, ethnicity,etc.), clinical, and environmental information that may influence theoutcome of the trait can be collected to further characterize and definethe sample set. In many cases, these factors are known to be associatedwith diseases and/or SNP allele frequencies. There are likelygene-environment and/or gene-gene interactions as well. Analysis methodsto address gene-environment and gene-gene interactions (for example, theeffects of the presence of both susceptibility alleles at two differentgenes can be greater than the effects of the individual alleles at twogenes combined) are discussed below.

After all the relevant phenotypic and genotypic information has beenobtained, statistical analyses are carried out to determine if there isany significant correlation between the presence of an allele or agenotype with the phenotypic characteristics of an individual.Preferably, data inspection and cleaning are first performed beforecarrying out statistical tests for genetic association. Epidemiologicaland clinical data of the samples can be summarized by descriptivestatistics with tables and graphs. Data validation is preferablyperformed to check for data completion, inconsistent entries, andoutliers. Chi-squared tests and t-tests (Wilcoxon rank-sum tests ifdistributions are not normal) may then be used to check for significantdifferences between cases and controls for discrete and continuousvariables, respectively. To ensure genotyping quality, Hardy-Weinbergdisequilibrium tests can be performed on cases and controls separately.Significant deviation from Hardy-Weinberg equilibrium (HWE) in bothcases and controls for individual markers can be indicative ofgenotyping errors. If HWE is violated in a majority of markers, it isindicative of population substructure that should be furtherinvestigated. Moreover, Hardy-Weinberg disequilibrium in cases only canindicate genetic association of the markers with the disease. B. Weir,Genetic Data Analysis, Sinauer (1990).

To test whether an allele of a single SNP is associated with the case orcontrol status of a phenotypic trait, one skilled in the art can compareallele frequencies in cases and controls. Standard chi-squared tests andFisher exact tests can be carried out on a 2×2 table (2 SNP alleles×2outcomes in the categorical trait of interest). To test whethergenotypes of a SNP are associated, chi-squared tests can be carried outon a 3×2 table (3 genotypes×2 outcomes). Score tests are also carriedout for genotypic association to contrast the three genotypicfrequencies (major homozygotes, heterozygotes and minor homozygotes) incases and controls, and to look for trends using 3 different modes ofinheritance, namely dominant (with contrast coefficients 2, −1, −1),additive or allelic (with contrast coefficients 1, 0, −1) and recessive(with contrast coefficients 1, 1, −2). Odds ratios for minor versusmajor alleles, and odds ratios for heterozygote and homozygote variantsversus the wild type genotypes are calculated with the desiredconfidence limits, usually 95%.

In order to control for confounders and to test for interaction andeffect modifiers, stratified analyses may be performed using stratifiedfactors that are likely to be confounding, including demographicinformation such as age, ethnicity, and gender, or an interactingelement or effect modifier, such as a known major gene (e.g., APOE forAlzheimer's disease or HLA genes for autoimmune diseases), orenvironmental factors such as smoking in lung cancer. Stratifiedassociation tests may be carried out using Cochran-Mantel-Haenszel teststhat take into account the ordinal nature of genotypes with 0, 1, and 2variant alleles. Exact tests by StatXact may also be performed whencomputationally possible. Another way to adjust for confounding effectsand test for interactions is to perform stepwise multiple logisticregression analysis using statistical packages such as SAS or R.Logistic regression is a model-building technique in which the bestfitting and most parsimonious model is built to describe the relationbetween the dichotomous outcome (for instance, getting a certain diseaseor not) and a set of independent variables (for instance, genotypes ofdifferent associated genes, and the associated demographic andenvironmental factors). The most common model is one in which the logittransformation of the odds ratios is expressed as a linear combinationof the variables (main effects) and their cross-product terms(interactions). Hosmer and Lemeshow, Applied Logistic Regression, Wiley(2000). To test whether a certain variable or interaction issignificantly associated with the outcome, coefficients in the model arefirst estimated and then tested for statistical significance of theirdeparture from zero.

In addition to performing association tests one marker at a time,haplotype association analysis may also be performed to study a numberof markers that are closely linked together. Haplotype association testscan have better power than genotypic or allelic association tests whenthe tested markers are not the disease-causing mutations themselves butare in linkage disequilibrium with such mutations. The test will even bemore powerful if the disease is indeed caused by a combination ofalleles on a haplotype (e.g., APOE is a haplotype formed by 2 SNPs thatare very close to each other). In order to perform haplotype associationeffectively, marker-marker linkage disequilibrium measures, both D′ andr², are typically calculated for the markers within a gene to elucidatethe haplotype structure. Recent studies in linkage disequilibriumindicate that SNPs within a gene are organized in block pattern, and ahigh degree of linkage disequilibrium exists within blocks and verylittle linkage disequilibrium exists between blocks. Daly et al, NatureGenetics 29:232-235 (2001). Haplotype association with the diseasestatus can be performed using such blocks once they have beenelucidated.

Haplotype association tests can be carried out in a similar fashion asthe allelic and genotypic association tests. Each haplotype in a gene isanalogous to an allele in a multi-allelic marker. One skilled in the artcan either compare the haplotype frequencies in cases and controls ortest genetic association with different pairs of haplotypes. It has beenproposed that score tests can be done on haplotypes using the program“haplo.score.” Schaid et al, Am J Hum Genet 70:425-434 (2002). In thatmethod, haplotypes are first inferred by EM algorithm and score testsare carried out with a generalized linear model (GLM) framework thatallows the adjustment of other factors.

An important decision in the performance of genetic association tests isthe determination of the significance level at which significantassociation can be declared when the P value of the tests reaches thatlevel. In an exploratory analysis where positive hits will be followedup in subsequent confirmatory testing, an unadjusted P value <0.2 (asignificance level on the lenient side), for example, may be used forgenerating hypotheses for significant association of a SNP with certainphenotypic characteristics of a disease. It is preferred that a p-value<0.05 (a significance level traditionally used in the art) is achievedin order for a SNP to be considered to have an association with adisease. It is more preferred that a p-value <0.01 (a significance levelon the stringent side) is achieved for an association to be declared.When hits are followed up in confirmatory analyses in more samples ofthe same source or in different samples from different sources,adjustment for multiple testing will be performed as to avoid excessnumber of hits while maintaining the experiment-wide error rates at0.05. While there are different methods to adjust for multiple testingto control for different kinds of error rates, a commonly used butrather conservative method is Bonferroni correction to control theexperiment-wise or family-wise error rate. Westfall et al., Multiplecomparisons and multiple tests, SAS Institute (1999). Permutation teststo control for the false discovery rates, FDR, can be more powerful.Benjamini and Hochberg, Journal of the Royal Statistical Society, SeriesB 57:1289-1300 (1995); Westfall and Young, Resampling-based MultipleTesting, Wiley (1993). Such methods to control for multiplicity would bepreferred when the tests are dependent and controlling for falsediscovery rates is sufficient as opposed to controlling for theexperiment-wise error rates.

In replication studies using samples from different populations afterstatistically significant markers have been identified in theexploratory stage, meta-analyses can then be performed by combiningevidence of different studies. Modern Epidemiology 643-673, Lippincott,Williams & Wilkins (1998). If available, association results known inthe art for the same SNPs can be included in the meta-analyses.

Since both genotyping and disease status classification can involveerrors, sensitivity analyses may be performed to see how odds ratios andp-values would change upon various estimates on genotyping and diseaseclassification error rates.

It has been well known that subpopulation-based sampling bias betweencases and controls can lead to spurious results in case-controlassociation studies when prevalence of the disease is associated withdifferent subpopulation groups. Ewens and Spielman, Am J Hum Genet62:450-458 (1995). Such bias can also lead to a loss of statisticalpower in genetic association studies. To detect populationstratification, Pritchard and Rosenberg suggested typing markers thatare unlinked to the disease and using results of association tests onthose markers to determine whether there is any populationstratification. Pritchard et al., Am J Hum Gen 65:220-228 (1999). Whenstratification is detected, the genomic control (GC) method as proposedby Devlin and Roeder can be used to adjust for the inflation of teststatistics due to population stratification. Devlin et al., Biometrics55:997-1004 (1999). The GC method is robust to changes in populationstructure levels as well as being applicable to DNA pooling designs.Devlin et al., Genet Epidem 21:273-284 (2001).

While Pritchard's method recommended using 15-20 unlinked microsatellitemarkers, it suggested using more than 30 biallelic markers to get enoughpower to detect population stratification. For the GC method, it hasbeen shown that about 60-70 biallelic markers are sufficient to estimatethe inflation factor for the test statistics due to populationstratification. Bacanu et al., Am J Hum Genet 66:1933-1944 (2000).Hence, 70 intergenic SNPs can be chosen in unlinked regions as indicatedin a genome scan. Kehoe et al., Hum Mol Genet 8:237-245 (1999).

Once individual risk factors, genetic or non-genetic, have been foundfor the predisposition to disease, the next step is to set up aclassification/prediction scheme to predict the category (for instance,disease or no-disease) that an individual will be in depending on hisgenotypes of associated SNPs and other non-genetic risk factors.Logistic regression for discrete trait and linear regression forcontinuous trait are standard techniques for such tasks. Draper andSmith, Applied Regression Analysis, Wiley (1998). Moreover, othertechniques can also be used for setting up classification. Suchtechniques include, but are not limited to, MART, CART, neural network,and discriminant analyses that are suitable for use in comparing theperformance of different methods. The Elements of Statistical Learning,Hastie, Tibshirani & Friedman, Springer (2002).

Disease Diagnosis and Predisposition Screening

Information on association/correlation between genotypes anddisease-related phenotypes can be exploited in several ways. Forexample, in the case of a highly statistically significant associationbetween one or more SNPs with predisposition to a disease for whichtreatment is available, detection of such a genotype pattern in anindividual may justify immediate administration of treatment, or atleast the institution of regular monitoring of the individual. Detectionof the susceptibility alleles associated with serious disease in acouple contemplating having children may also be valuable to the couplein their reproductive decisions. In the case of a weaker but stillstatistically significant association between a SNP and a human disease,immediate therapeutic intervention or monitoring may not be justifiedafter detecting the susceptibility allele or SNP. Nevertheless, thesubject can be motivated to begin simple life-style changes (e.g., diet,exercise) that can be accomplished at little or no cost to theindividual but would confer potential benefits in reducing the risk ofdeveloping conditions for which that individual may have an increasedrisk by virtue of having the risk allele(s).

The SNPs of the invention may contribute to the development of CHD(e.g., MI) or aneurysm/dissection, or to responsiveness of an individualto statin treatment, in different ways. Some polymorphisms occur withina protein coding sequence and contribute to disease phenotype byaffecting protein structure. Other polymorphisms occur in noncodingregions but may exert phenotypic effects indirectly via influence on,for example, replication, transcription, and/or translation. A singleSNP may affect more than one phenotypic trait. Likewise, a singlephenotypic trait may be affected by multiple SNPs in different genes.

As used herein, the terms “diagnose,” “diagnosis,” and “diagnostics”include, but are not limited to, any of the following: detection of CHDor aneurysm/dissection that an individual may presently have,predisposition/susceptibility/predictive screening (i.e., determiningwhether an individual has an increased or decreased risk of developingCHD or aneurysm/dissection in the future), prognosing the future courseof CHD or aneurysm/dissection or recurrence of CHD oraneurysm/dissection in an individual, determining a particular type orsubclass of CHD or aneurysm/dissection in an individual who currently orpreviously had CHD or aneurysm/dissection, confirming or reinforcing apreviously made diagnosis of CHD or aneurysm/dissection, evaluating anindividual's likelihood of responding positively to a particulartreatment or therapeutic agent such as statin treatment (particularlytreatment or prevention of CHD or aneurysm/dissection using statins),determining or selecting a therapeutic or preventive strategy that anindividual is most likely to positively respond to (e.g., selecting aparticular therapeutic agent such as a statin, or combination oftherapeutic agents, or determining a dosing regimen, etc.), classifying(or confirming/reinforcing) an individual as a responder/non-responder(or determining a particular subtype of responder/non-responder) withrespect to the individual's response to a drug treatment such as statintreatment, and predicting whether a patient is likely to experiencetoxic effects from a particular treatment or therapeutic compound. Suchdiagnostic uses can be based on the SNPs individually or in a uniquecombination or SNP haplotypes of the present invention.

Haplotypes are particularly useful in that, for example, fewer SNPs canbe genotyped to determine if a particular genomic region harbors a locusthat influences a particular phenotype, such as in linkagedisequilibrium-based SNP association analysis.

Linkage disequilibrium (LD) refers to the co-inheritance of alleles(e.g., alternative nucleotides) at two or more different SNP sites atfrequencies greater than would be expected from the separate frequenciesof occurrence of each allele in a given population. The expectedfrequency of co-occurrence of two alleles that are inheritedindependently is the frequency of the first allele multiplied by thefrequency of the second allele. Alleles that co-occur at expectedfrequencies are said to be in “linkage equilibrium.” In contrast, LDrefers to any non-random genetic association between allele(s) at two ormore different SNP sites, which is generally due to the physicalproximity of the two loci along a chromosome. LD can occur when two ormore SNPs sites are in close physical proximity to each other on a givenchromosome and therefore alleles at these SNP sites will tend to remainunseparated for multiple generations with the consequence that aparticular nucleotide (allele) at one SNP site will show a non-randomassociation with a particular nucleotide (allele) at a different SNPsite located nearby. Hence, genotyping one of the SNP sites will givealmost the same information as genotyping the other SNP site that is inLD.

Various degrees of LD can be encountered between two or more SNPs withthe result being that some SNPs are more closely associated (i.e., instronger LD) than others. Furthermore, the physical distance over whichLD extends along a chromosome differs between different regions of thegenome, and therefore the degree of physical separation between two ormore SNP sites necessary for LD to occur can differ between differentregions of the genome.

For diagnostic purposes and similar uses, if a particular SNP site isfound to be useful for, for example, predicting an individual'ssusceptibility to CHD or aneurysm/dissection or an individual's responseto statin treatment, then the skilled artisan would recognize that otherSNP sites which are in LD with this SNP site would also be useful forthe same purposes. Thus, polymorphisms (e.g., SNPs and/or haplotypes)that are not the actual disease-causing (causative) polymorphisms, butare in LD with such causative polymorphisms, are also useful. In suchinstances, the genotype of the polymorphism(s) that is/are in LD withthe causative polymorphism is predictive of the genotype of thecausative polymorphism and, consequently, predictive of the phenotype(e.g., CHD, aneurysm/dissection, or responder/non-responder to statintreatment) that is influenced by the causative SNP(s). Therefore,polymorphic markers that are in LD with causative polymorphisms areuseful as diagnostic markers, and are particularly useful when theactual causative polymorphism(s) is/are unknown.

Examples of polymorphisms that can be in LD with one or more causativepolymorphisms (and/or in LD with one or more polymorphisms that have asignificant statistical association with a condition) and thereforeuseful for diagnosing the same condition that the causative/associatedSNP(s) is used to diagnose, include other SNPs in the same gene,protein-coding, or mRNA transcript-coding region as thecausative/associated SNP, other SNPs in the same exon or same intron asthe causative/associated SNP, other SNPs in the same haplotype block asthe causative/associated SNP, other SNPs in the same intergenic regionas the causative/associated SNP, SNPs that are outside but near a gene(e.g., within 6 kb on either side, 5′ or 3′, of a gene boundary) thatharbors a causative/associated SNP, etc. Such useful LD SNPs can beselected from among the SNPs disclosed in Tables 1 and 2, for example.

Linkage disequilibrium in the human genome is reviewed in Wall et al.,“Haplotype blocks and linkage disequilibrium in the human genome,” NatRev Genet 4(8):587-97 (August 2003); Garner et al., “On selectingmarkers for association studies: patterns of linkage disequilibriumbetween two and three diallelic loci,” Genet Epidemiol 24(1):57-67(January 2003); Ardlie et al., “Patterns of linkage disequilibrium inthe human genome,” Nat Rev Genet 3(4):299-309 (April 2002); erratum inNat Rev Genet 3(7):566 (July 2002); and Remm et al., “High-densitygenotyping and linkage disequilibrium in the human genome usingchromosome 22 as a model,” Curr Opin Chem Biol 6(1):24-30 (February2002); J. B. S. Haldane, “The combination of linkage values, and thecalculation of distances between the loci of linked factors,” J Genet8:299-309 (1919); G. Mendel, Versuche über Pflanzen-Hybriden.Verhandlungen des naturforschenden Vereines in Brünn (Proceedings of theNatural History Society of Brünn) (1866); Genes IV, B. Lewin, ed.,Oxford University Press, N.Y. (1990); D. L. Hartl and A. G. ClarkPrinciples of Population Genetics 2^(nd) ed., Sinauer Associates, Inc.,Mass. (1989); J. H. Gillespie Population Genetics: A Concise Guide.2^(nd) ed., Johns Hopkins University Press (2004); R. C. Lewontin, “Theinteraction of selection and linkage. I. General considerations;heterotic models,” Genetics 49:49-67 (1964); P. G. Hoel, Introduction toMathematical Statistics 2^(nd) ed., John Wiley & Sons, Inc., N.Y.(1954); R. R. Hudson, “Two-locus sampling distributions and theirapplication,” Genetics 159:1805-1817 (2001); A. P. Dempster, N. M.Laird, D. B. Rubin, “Maximum likelihood from incomplete data via the EMalgorithm,” J R Stat Soc 39:1-38 (1977); L. Excoffier, M. Slatkin,“Maximum-likelihood estimation of molecular haplotype frequencies in adiploid population,” Mol Biol Evol 12(5):921-927 (1995); D. A. Tregouet,S. Escolano, L. Tiret, A. Mallet, J. L. Golmard, “A new algorithm forhaplotype-based association analysis: the Stochastic-EM algorithm,” AnnHum Genet 68(Pt 2):165-177 (2004); A. D. Long and C. H. Langley C H,“The power of association studies to detect the contribution ofcandidate genetic loci to variation in complex traits,” Genome Research9:720-731 (1999); A. Agresti, Categorical Data Analysis, John Wiley &Sons, Inc., N.Y. (1990); K. Lange, Mathematical and Statistical Methodsfor Genetic Analysis, Springer-Verlag New York, Inc., N.Y. (1997); TheInternational HapMap Consortium, “The International HapMap Project,”Nature 426:789-796 (2003); The International HapMap Consortium, “Ahaplotype map of the human genome,” Nature 437:1299-1320 (2005); G. A.Thorisson, A. V. Smith, L. Krishnan, L. D. Stein, “The InternationalHapMap Project Web Site,” Genome Research 15:1591-1593 (2005); G.McVean, C. C. A. Spencer, R. Chaix, “Perspectives on human geneticvariation from the HapMap project,” PLoS Genetics 1(4):413-418 (2005);J. N. Hirschhorn, M. J. Daly, “Genome-wide association studies forcommon diseases and complex traits,” Nat Genet 6:95-108 (2005); S. J.Schrodi, “A probabilistic approach to large-scale association scans: asemi-Bayesian method to detect disease-predisposing alleles,” SAGMB4(1):31 (2005); W. Y. S. Wang, B. J. Barratt, D. G. Clayton, J. A. Todd,“Genome-wide association studies: theoretical and practical concerns,”Nat Rev Genet 6:109-118 (2005); J. K. Pritchard, M. Przeworski, “Linkagedisequilibrium in humans: models and data,” Am J Hum Genet 69:1-14(2001).

As discussed above, one aspect of the present invention is the discoverythat SNPs that are in certain LD distance with an interrogated SNP canalso be used as valid markers for determining whether an individual hasan increased or decreased risk of having or developing CHD oraneurysm/dissection, or an individual's likelihood of benefiting from adrug treatment such as statin treatment. As used herein, the term“interrogated SNP” refers to SNPs that have been found to be associatedwith an increased or decreased risk of disease using genotyping resultsand analysis, or other appropriate experimental method as exemplified inthe working examples described in this application. As used herein, theterm “LD SNP” refers to a SNP that has been characterized as a SNPassociating with an increased or decreased risk of diseases due to theirbeing in LD with the “interrogated SNP” under the methods of calculationdescribed in the application. Below, applicants describe the methods ofcalculation with which one of ordinary skilled in the art may determineif a particular SNP is in LD with an interrogated SNP. The parameter r²is commonly used in the genetics art to characterize the extent oflinkage disequilibrium between markers (Hudson, 2001). As used herein,the term “in LD with” refers to a particular SNP that is measured atabove the threshold of a parameter such as r² with an interrogated SNP.

It is now common place to directly observe genetic variants in a sampleof chromosomes obtained from a population. Suppose one has genotype dataat two genetic markers located on the same chromosome, for the markers Aand B. Further suppose that two alleles segregate at each of these twomarkers such that alleles A₁ and A₂ can be found at marker A and allelesB₁ and B₂ at marker B. Also assume that these two markers are on a humanautosome. If one is to examine a specific individual and find that theyare heterozygous at both markers, such that their two-marker genotype isA₁A₂B₁B₂, then there are two possible configurations: the individual inquestion could have the alleles A₁B₁ on one chromosome and A₂B₂ on theremaining chromosome; alternatively, the individual could have allelesA₁B₂ on one chromosome and A₂B₁ on the other. The arrangement of alleleson a chromosome is called a haplotype. In this illustration, theindividual could have haplotypes A₁B₁/A₂B₂ or A₁B₂/A₂B₁ (see Hartl andClark (1989) for a more complete description). The concept of linkageequilibrium relates the frequency of haplotypes to the allelefrequencies.

Assume that a sample of individuals is selected from a largerpopulation. Considering the two markers described above, each having twoalleles, there are four possible haplotypes: A₁B₁, A₁B₂, A₂B₁ and A₂B₂.Denote the frequencies of these four haplotypes with the followingnotation.

P ₁₁=freq(A ₁ B ₁)  (1)

P ₁₂=freq(A ₁ B ₂)  (2)

P ₂₁=freq(A ₂ B ₁)  (3)

P ₂₂=freq(A ₂ B ₂)  (4)

The allele frequencies at the two markers are then the sum of differenthaplotype frequencies, it is straightforward to write down a similar setof equations relating single-marker allele frequencies to two-markerhaplotype frequencies:

p ₁=freq(A ₁)=P ₁₁ +P ₁₂  (5)

p ₂=freq(A ₂)=P ₂₁ +P ₂₂  (6)

q ₁=freq(B ₁)=P ₁₁ +P ₂₁  (7)

q ₂=freq(B ₂)=P ₁₂ +P ₂₂  (8)

Note that the four haplotype frequencies and the allele frequencies ateach marker must sum to a frequency of 1.

P ₁₁ +P ₁₂ +P ₂₁ +P ₂₂=1  (9)

p ₁ +p ₂=1  (10)

q ₁ +q ₂=1  (11)

If there is no correlation between the alleles at the two markers, onewould expect that the frequency of the haplotypes would be approximatelythe product of the composite alleles. Therefore,

P ₁₁ ≈p ₁ q ₁  (12)

P ₁₂ ≈p ₁ q ₂  (13)

P ₂₁ ≈p ₂ q ₁  (14)

P ₂₂ ≈p ₂ q ₂  (15)

These approximating equations (12)-(15) represent the concept of linkageequilibrium where there is independent assortment between the twomarkers—the alleles at the two markers occur together at random. Theseare represented as approximations because linkage equilibrium andlinkage disequilibrium are concepts typically thought of as propertiesof a sample of chromosomes; and as such they are susceptible tostochastic fluctuations due to the sampling process. Empirically, manypairs of genetic markers will be in linkage equilibrium, but certainlynot all pairs.

Having established the concept of linkage equilibrium above, applicantscan now describe the concept of linkage disequilibrium (LD), which isthe deviation from linkage equilibrium. Since the frequency of the A₁B₁haplotype is approximately the product of the allele frequencies for A₁and B₁ under the assumption of linkage equilibrium as statedmathematically in (12), a simple measure for the amount of departurefrom linkage equilibrium is the difference in these two quantities, D,

D=P ₁₁ −p ₁ q ₁  (16)

D=0 indicates perfect linkage equilibrium. Substantial departures fromD=0 indicates LD in the sample of chromosomes examined. Many propertiesof D are discussed in Lewontin (1964) including the maximum and minimumvalues that D can take. Mathematically, using basic algebra, it can beshown that D can also be written solely in terms of haplotypes:

D=P ₁₁ P ₂₂ −P ₁₂ P ₂₁  (17)

If one transforms D by squaring it and subsequently dividing by theproduct of the allele frequencies of A₁, A₂, B₁ and B₂, the resultingquantity, called r², is equivalent to the square of the Pearson'scorrelation coefficient commonly used in statistics (e.g. Hoel, 1954).

$\begin{matrix}{r^{2} = \frac{D^{2}}{p_{1}p_{2}q_{1}q_{2}}} & (18)\end{matrix}$

As with D, values of r² close to 0 indicate linkage equilibrium betweenthe two markers examined in the sample set. As values of r² increase,the two markers are said to be in linkage disequilibrium. The range ofvalues that r² can take are from 0 to 1. r²=1 when there is a perfectcorrelation between the alleles at the two markers.

In addition, the quantities discussed above are sample-specific. And assuch, it is necessary to formulate notation specific to the samplesstudied. In the approach discussed here, three types of samples are ofprimary interest: (i) a sample of chromosomes from individuals affectedby a disease-related phenotype (cases), (ii) a sample of chromosomesobtained from individuals not affected by the disease-related phenotype(controls), and (iii) a standard sample set used for the construction ofhaplotypes and calculation pairwise linkage disequilibrium. For theallele frequencies used in the development of the method describedbelow, an additional subscript will be added to denote either the caseor control sample sets.

p _(1,cs)=freq(A ₁ in cases)  (19)

p _(2,cs)=freq(A ₂ in cases)  (20)

q _(1,cs)=freq(B ₁ in cases)  (21)

q _(2,cs)=freq(B ₂ in cases)  (22)

Similarly,

p _(1,ct)=freq(A ₁ in controls)  (23)

p _(2,ct)=freq(A ₂ in controls)  (24)

q _(1,ct)=freq(B ₁ in controls)  (25)

q _(2,ct)=freq(B ₂ in controls)  (26)

As a well-accepted sample set is necessary for robust linkagedisequilibrium calculations, data obtained from the International HapMapproject (The International HapMap Consortium 2003, 2005; Thorisson etal, 2005; McVean et al, 2005) can be used for the calculation ofpairwise r² values. Indeed, the samples genotyped for the InternationalHapMap Project were selected to be representative examples from varioushuman sub-populations with sufficient numbers of chromosomes examined todraw meaningful and robust conclusions from the patterns of geneticvariation observed. The International HapMap project website(hapmap.org) contains a description of the project, methods utilized andsamples examined. It is useful to examine empirical data to get a senseof the patterns present in such data.

Haplotype frequencies were explicit arguments in equation (18) above.However, knowing the 2-marker haplotype frequencies requires that phaseto be determined for doubly heterozygous samples. When phase is unknownin the data examined, various algorithms can be used to infer phase fromthe genotype data. This issue was discussed earlier where the doublyheterozygous individual with a 2-SNP genotype of A₁A₂B₁B₂ could have oneof two different sets of chromosomes: A₁B₁/A₂B₂ or AB₂/A₂B₁. One suchalgorithm to estimate haplotype frequencies is theexpectation-maximization (EM) algorithm first formalized by Dempster etal. (1977). This algorithm is often used in genetics to infer haplotypefrequencies from genotype data (e.g. Excoffier and Slatkin (1995);Tregouet et al. (2004)). It should be noted that for the two-SNP caseexplored here, EM algorithms have very little error provided that theallele frequencies and sample sizes are not too small. The impact on r²values is typically negligible.

As correlated genetic markers share information, interrogation of SNPmarkers in LD with a disease-associated SNP marker can also havesufficient power to detect disease association (Long and Langley(1999)). The relationship between the power to directly finddisease-associated alleles and the power to indirectly detectdisease-association was investigated by Pritchard and Przeworski (2001).In a straight-forward derivation, it can be shown that the power todetect disease association indirectly at a marker locus in linkagedisequilibrium with a disease-association locus is approximately thesame as the power to detect disease-association directly at thedisease-association locus if the sample size is increased by a factor of

$\frac{1}{r^{2}}$

(the reciprocal of equation 18) at the marker in comparison with thedisease-association locus.

Therefore, if one calculated the power to detect disease-associationindirectly with an experiment having N samples, then equivalent power todirectly detect disease-association (at the actualdisease-susceptibility locus) would necessitate an experiment usingapproximately r²N samples. This elementary relationship between power,sample size and linkage disequilibrium can be used to derive an r²threshold value useful in determining whether or not genotyping markersin linkage disequilibrium with a SNP marker directly associated withdisease status has enough power to indirectly detectdisease-association.

To commence a derivation of the power to detect disease-associatedmarkers through an indirect process, define the effective chromosomalsample size as

$\begin{matrix}{{n = \frac{4N_{cs}N_{ct}}{N_{cs} + N_{ct}}};} & (27)\end{matrix}$

where N_(cs) and N_(ct) are the numbers of diploid cases and controls,respectively. This is necessary to handle situations where the numbersof cases and controls are not equivalent. For equal case and controlsample sizes, N_(cs)=N_(ct)=N, the value of the effective number ofchromosomes is simply n=2N−as expected. Let power be calculated for asignificance level α (such that traditional P-values below α will bedeemed statistically significant). Define the standard Gaussiandistribution function as Φ(•). Mathematically,

$\begin{matrix}{{\Phi (x)} = {\frac{1}{\sqrt{2\pi}}{\int_{- \infty}^{X}{e^{\frac{\theta^{2}}{2}}d\mspace{11mu} \theta}}}} & (28)\end{matrix}$

Alternatively, the following error function notation (Erf) may also beused,

$\begin{matrix}{{\Phi (x)} = {\frac{1}{2}\left\lbrack {1 + {{Erf}\mspace{11mu} \left( \frac{x}{\sqrt{2}} \right)}} \right\rbrack}} & (29)\end{matrix}$

For example, Φ(1.644854)=0.95. The value of r² may be derived to yield apre-specified minimum amount of power to detect disease associationthough indirect interrogation. Noting that the LD SNP marker could bethe one that is carrying the disease-association allele, therefore thatthis approach constitutes a lower-bound model where all indirect powerresults are expected to be at least as large as those interrogated.

Denote by β the error rate for not detecting truly disease-associatedmarkers. Therefore, 1−β is the classical definition of statisticalpower. Substituting the Pritchard-Pzreworski result into the samplesize, the power to detect disease association at a significance level ofα is given by the approximation

$\begin{matrix}{{{1 - \beta} \cong {\Phi\left\lbrack {\frac{{q_{1,{cs}} - q_{1,{ct}}}}{\sqrt{\frac{{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}}{r^{2}n}}} - Z_{1 - \frac{\alpha}{2}}} \right\rbrack}};} & (30)\end{matrix}$

where Z_(u) is the inverse of the standard normal cumulativedistribution evaluated at u(u∈(0,1)). Z_(u)=Φ⁻¹(u), where Φ(Φ⁻¹(u))=Φ⁻¹(Φ(u))=u. For example, setting α=0.05, and therefore 1−α/2=0.975, oneobtains Z_(0.975)=1.95996. Next, setting power equal to a threshold of aminimum power of T,

$\begin{matrix}{T = {\Phi\left\lbrack {\frac{{q_{1,{cs}} - q_{1,{ct}}}}{\sqrt{\frac{{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}}{r^{2}n}}} - Z_{1 - \frac{\alpha}{2}}} \right\rbrack}} & (31)\end{matrix}$

and solving for r², the following threshold r² is obtained:

$\begin{matrix}{r_{T}^{2} = {\frac{\left\lfloor {{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}} \right\rfloor}{{n\left( {q_{1,{cs}} - q_{1,{ct}}} \right)}^{2}}\left\lbrack {{\Phi^{- 1}(T)} + Z_{1 - \frac{\alpha}{2}}} \right\rbrack}^{2}} & (32) \\{{Or},} & \; \\{r_{T}^{2} = {\frac{\left( {Z_{T} + Z_{1 - \frac{\alpha}{2}}} \right)^{2}}{n}\left\lbrack \frac{q_{1,{cs}} - \left( q_{1,{cs}} \right)^{2} + q_{1,{ct}} - \left( q_{1,{ct}} \right)^{2}}{\left( {q_{1,{cs}} - q_{1,{ct}}} \right)^{2}} \right\rbrack}} & (33)\end{matrix}$

Suppose that r² is calculated between an interrogated SNP and a numberof other SNPs with varying levels of LD with the interrogated SNP. Thethreshold value r_(T) ² is the minimum value of linkage disequilibriumbetween the interrogated SNP and the potential LD SNPs such that the LDSNP still retains a power greater or equal to T for detectingdisease-association. For example, suppose that SNP rs200 is genotyped ina case-control disease-association study and it is found to beassociated with a disease phenotype. Further suppose that the minorallele frequency in 1,000 case chromosomes was found to be 16% incontrast with a minor allele frequency of 10% in 1,000 controlchromosomes. Given those measurements one could have predicted, prior tothe experiment, that the power to detect disease association at asignificance level of 0.05 was quite high—approximately 98% using a testof allelic association. Applying equation (32) one can calculate aminimum value of r² to indirectly assess disease association assumingthat the minor allele at SNP rs200 is truly disease-predisposing for athreshold level of power. If one sets the threshold level of power to be80%, then r_(T) ²=0.489 given the same significance level and chromosomenumbers as above. Hence, any SNP with a pairwise r² value with rs200greater than 0.489 is expected to have greater than 80% power to detectthe disease association. Further, this is assuming the conservativemodel where the LD SNP is disease-associated only through linkagedisequilibrium with the interrogated SNP rs200.

The contribution or association of particular SNPs and/or SNP haplotypeswith disease phenotypes, such as CHD or aneurysm/dissection, enables theSNPs of the present invention to be used to develop superior diagnostictests capable of identifying individuals who express a detectable trait,such as CHD or aneurysm/dissection, as the result of a specificgenotype, or individuals whose genotype places them at an increased ordecreased risk of developing a detectable trait at a subsequent time ascompared to individuals who do not have that genotype. As describedherein, diagnostics may be based on a single SNP or a group of SNPs.Combined detection of a plurality of SNPs (for example, 2, 3, 4, 5, 6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25, 30, 32, 48,50, 64, 96, 100, or any other number in-between, or more, of the SNPsprovided in Table 1 and/or Table 2) typically increases the probabilityof an accurate diagnosis. For example, the presence of a single SNPknown to correlate with CHD might indicate a probability of 20% that anindividual has or is at risk of developing CHD, whereas detection offive SNPs, each of which correlates with CHD, might indicate aprobability of 80% that an individual has or is at risk of developingCHD. To further increase the accuracy of diagnosis or predispositionscreening, analysis of the SNPs of the present invention can be combinedwith that of other polymorphisms or other risk factors of CHD oraneurysm/dissection, such as disease symptoms, pathologicalcharacteristics, family history, diet, environmental factors orlifestyle factors.

It will, of course, be understood by practitioners skilled in thetreatment or diagnosis of CHD or aneurysm/dissection that the presentinvention generally does not intend to provide an absoluteidentification of individuals who are at risk (or less at risk) ofdeveloping CHD or aneurysm/dissection, and/or pathologies related to CHDor aneurysm/dissection, but rather to indicate a certain increased (ordecreased) degree or likelihood of developing the disease based onstatistically significant association results. However, this informationis extremely valuable as it can be used to, for example, initiatepreventive treatments or to allow an individual carrying one or moresignificant SNPs or SNP haplotypes to foresee warning signs such asminor clinical symptoms, or to have regularly scheduled physical examsto monitor for appearance of a condition in order to identify and begintreatment of the condition at an early stage. Particularly with diseasesthat are extremely debilitating or fatal if not treated on time, theknowledge of a potential predisposition, even if this predisposition isnot absolute, would likely contribute in a very significant manner totreatment efficacy.

The diagnostic techniques of the present invention may employ a varietyof methodologies to determine whether a test subject has a SNP or a SNPpattern associated with an increased or decreased risk of developing adetectable trait or whether the individual suffers from a detectabletrait as a result of a particular polymorphism/mutation, including, forexample, methods which enable the analysis of individual chromosomes forhaplotyping, family studies, single sperm DNA analysis, or somatichybrids. The trait analyzed using the diagnostics of the invention maybe any detectable trait that is commonly observed in pathologies anddisorders related to CHD or aneurysm/dissection.

Another aspect of the present invention relates to a method ofdetermining whether an individual is at risk (or less at risk) ofdeveloping one or more traits or whether an individual expresses one ormore traits as a consequence of possessing a particular trait-causing ortrait-influencing allele. These methods generally involve obtaining anucleic acid sample from an individual and assaying the nucleic acidsample to determine which nucleotide(s) is/are present at one or moreSNP positions, wherein the assayed nucleotide(s) is/are indicative of anincreased or decreased risk of developing the trait or indicative thatthe individual expresses the trait as a result of possessing aparticular trait-causing or trait-influencing allele.

In another embodiment, the SNP detection reagents of the presentinvention are used to determine whether an individual has one or moreSNP allele(s) affecting the level (e.g., the concentration of mRNA orprotein in a sample, etc.) or pattern (e.g., the kinetics of expression,rate of decomposition, stability profile, Km, Vmax, etc.) of geneexpression (collectively, the “gene response” of a cell or bodilyfluid). Such a determination can be accomplished by screening for mRNAor protein expression (e.g., by using nucleic acid arrays, RT-PCR,TaqMan assays, or mass spectrometry), identifying genes having alteredexpression in an individual, genotyping SNPs disclosed in Table 1 and/orTable 2 that could affect the expression of the genes having alteredexpression (e.g., SNPs that are in and/or around the gene(s) havingaltered expression, SNPs in regulatory/control regions, SNPs in and/oraround other genes that are involved in pathways that could affect theexpression of the gene(s) having altered expression, or all SNPs couldbe genotyped), and correlating SNP genotypes with altered geneexpression. In this manner, specific SNP alleles at particular SNP sitescan be identified that affect gene expression.

Pharmacogenomics and Therapeutics/Drug Development

The present invention provides methods for assessing thepharmacogenomics of a subject harboring particular SNP alleles orhaplotypes to a particular therapeutic agent or pharmaceutical compound,or to a class of such compounds. Pharmacogenomics deals with the roleswhich clinically significant hereditary variations (e.g., SNPs) play inthe response to drugs due to altered drug disposition and/or abnormalaction in affected persons. See, e.g., Roses, Nature 405, 857-865(2000); Gould Rothberg, Nature Biotechnology 19, 209-211 (2001);Eichelbaum, Clin Exp Pharmacol Physiol 23(10-11):983-985 (1996); andLinder, Clin Chem 43(2):254-266 (1997). The clinical outcomes of thesevariations can result in severe toxicity of therapeutic drugs in certainindividuals or therapeutic failure of drugs in certain individuals as aresult of individual variation in metabolism. Thus, the SNP genotype ofan individual can determine the way a therapeutic compound acts on thebody or the way the body metabolizes the compound. For example, SNPs indrug metabolizing enzymes can affect the activity of these enzymes,which in turn can affect both the intensity and duration of drug action,as well as drug metabolism and clearance.

The discovery of SNPs in drug metabolizing enzymes, drug transporters,proteins for pharmaceutical agents, and other drug targets has explainedwhy some patients do not obtain the expected drug effects, show anexaggerated drug effect, or experience serious toxicity from standarddrug dosages. SNPs can be expressed in the phenotype of the extensivemetabolizer and in the phenotype of the poor metabolizer. Accordingly,SNPs may lead to allelic variants of a protein in which one or more ofthe protein functions in one population are different from those inanother population. SNPs and the encoded variant peptides thus providetargets to ascertain a genetic predisposition that can affect treatmentmodality. For example, in a ligand-based treatment, SNPs may give riseto amino terminal extracellular domains and/or other ligand-bindingregions of a receptor that are more or less active in ligand binding,thereby affecting subsequent protein activation. Accordingly, liganddosage would necessarily be modified to maximize the therapeutic effectwithin a given population containing particular SNP alleles orhaplotypes.

As an alternative to genotyping, specific variant proteins containingvariant amino acid sequences encoded by alternative SNP alleles could beidentified. Thus, pharmacogenomic characterization of an individualpermits the selection of effective compounds and effective dosages ofsuch compounds for prophylactic or therapeutic uses based on theindividual's SNP genotype, thereby enhancing and optimizing theeffectiveness of the therapy. Furthermore, the production of recombinantcells and transgenic animals containing particular SNPs/haplotypes alloweffective clinical design and testing of treatment compounds and dosageregimens. For example, transgenic animals can be produced that differonly in specific SNP alleles in a gene that is orthologous to a humandisease susceptibility gene.

Pharmacogenomic uses of the SNPs of the present invention provideseveral significant advantages for patient care, particularly inpredicting an individual's predisposition to CHD (e.g., MI) oraneurysm/dissection and in predicting an individual's responsiveness tothe use of statin (particularly for treating or preventing CHD oraneurysm/dissection). Pharmacogenomic characterization of an individual,based on an individual's SNP genotype, can identify those individualsunlikely to respond to treatment with a particular medication andthereby allows physicians to avoid prescribing the ineffectivemedication to those individuals. On the other hand, SNP genotyping of anindividual may enable physicians to select the appropriate medicationand dosage regimen that will be most effective based on an individual'sSNP genotype. This information increases a physician's confidence inprescribing medications and motivates patients to comply with their drugregimens. Furthermore, pharmacogenomics may identify patientspredisposed to toxicity and adverse reactions to particular drugs ordrug dosages. Adverse drug reactions lead to more than 100,000 avoidabledeaths per year in the United States alone and therefore represent asignificant cause of hospitalization and death, as well as a significanteconomic burden on the healthcare system (Pfost et al., Trends inBiotechnology, August 2000.). Thus, pharmacogenomics based on the SNPsdisclosed herein has the potential to both save lives and reducehealthcare costs substantially.

Pharmacogenomics in general is discussed further in Rose et al.,“Pharmacogenetic analysis of clinically relevant genetic polymorphisms,”Methods Mol Med 85:225-37 (2003). Pharmacogenomics as it relates toAlzheimer's disease and other neurodegenerative disorders is discussedin Cacabelos, “Pharmacogenomics for the treatment of dementia,” Ann Med34(5):357-79 (2002); Maimone et al., “Pharmacogenomics ofneurodegenerative diseases,” Eur J Pharmacol 413(1):11-29 (February2001); and Poirier, “Apolipoprotein E: a pharmacogenetic target for thetreatment of Alzheimer's disease,” Mol Diagn 4(4):335-41 (December1999). Pharmacogenomics as it relates to cardiovascular disorders isdiscussed in Siest et al., “Pharmacogenomics of drugs affecting thecardiovascular system,” Clin Chem Lab Med 41(4):590-9 (April 2003);Mukherjee et al., “Pharmacogenomics in cardiovascular diseases,” ProgCardiovasc Dis 44(6):479-98 (May-June 2002); and Mooser et al.,“Cardiovascular pharmacogenetics in the SNP era,” J Thromb Haemost1(7):1398-402 (July 2003). Pharmacogenomics as it relates to cancer isdiscussed in McLeod et al., “Cancer pharmacogenomics: SNPs, chips, andthe individual patient,” Cancer Invest 21(4):630-40 (2003); and Watterset al., “Cancer pharmacogenomics: current and future applications,”Biochim BiophysActa 1603(2):99-111 (March 2003).

The SNPs of the present invention also can be used to identify noveltherapeutic targets for CHD or aneurysm/dissection. For example, genescontaining the disease-associated variants (“variant genes”) or theirproducts, as well as genes or their products that are directly orindirectly regulated by or interacting with these variant genes or theirproducts, can be targeted for the development of therapeutics that, forexample, treat the disease or prevent or delay disease onset. Thetherapeutics may be composed of, for example, small molecules, proteins,protein fragments or peptides, antibodies, nucleic acids, or theirderivatives or mimetics which modulate the functions or levels of thetarget genes or gene products.

The SNP-containing nucleic acid molecules disclosed herein, and theircomplementary nucleic acid molecules, may be used as antisenseconstructs to control gene expression in cells, tissues, and organisms.Antisense technology is well established in the art and extensivelyreviewed in Antisense Drug Technology: Principles, Strategies, andApplications, Crooke, ed., Marcel Dekker, Inc., N.Y. (2001). Anantisense nucleic acid molecule is generally designed to becomplementary to a region of mRNA expressed by a gene so that theantisense molecule hybridizes to the mRNA and thereby blocks translationof mRNA into protein. Various classes of antisense oligonucleotides areused in the art, two of which are cleavers and blockers. Cleavers, bybinding to target RNAs, activate intracellular nucleases (e.g., RNaseHor RNase L) that cleave the target RNA. Blockers, which also bind totarget RNAs, inhibit protein translation through steric hindrance ofribosomes. Exemplary blockers include peptide nucleic acids,morpholinos, locked nucleic acids, and methylphosphonates. See, e.g.,Thompson, Drug Discovery Today 7(17): 912-917 (2002). Antisenseoligonucleotides are directly useful as therapeutic agents, and are alsouseful for determining and validating gene function (e.g., in geneknock-out or knock-down experiments).

Antisense technology is further reviewed in: Lavery et al., “Antisenseand RNAi: powerful tools in drug target discovery and validation,” CurrOpin Drug Discov Devel 6(4):561-9 (July 2003); Stephens et al.,“Antisense oligonucleotide therapy in cancer,” Curr Opin Mol Ther5(2):118-22 (April 2003); Kurreck, “Antisense technologies. Improvementthrough novel chemical modifications,” Eur J Biochem 270(8):1628-44(April 2003); Dias et al., “Antisense oligonucleotides: basic conceptsand mechanisms,” Mol Cancer Ther 1(5):347-55 (March 2002); Chen,“Clinical development of antisense oligonucleotides as anti-cancertherapeutics,” Methods Mol Med 75:621-36 (2003); Wang et al., “Antisenseanticancer oligonucleotide therapeutics,” Curr Cancer Drug Targets1(3):177-96 (November 2001); and Bennett, “Efficiency of antisenseoligonucleotide drug discovery,” Antisense Nucleic Acid Drug Dev12(3):215-24 (June 2002).

The SNPs of the present invention are particularly useful for designingantisense reagents that are specific for particular nucleic acidvariants. Based on the SNP information disclosed herein, antisenseoligonucleotides can be produced that specifically target mRNA moleculesthat contain one or more particular SNP nucleotides. In this manner,expression of mRNA molecules that contain one or more undesiredpolymorphisms (e.g., SNP nucleotides that lead to a defective proteinsuch as an amino acid substitution in a catalytic domain) can beinhibited or completely blocked. Thus, antisense oligonucleotides can beused to specifically bind a particular polymorphic form (e.g., a SNPallele that encodes a defective protein), thereby inhibiting translationof this form, but which do not bind an alternative polymorphic form(e.g., an alternative SNP nucleotide that encodes a protein havingnormal function).

Antisense molecules can be used to inactivate mRNA in order to inhibitgene expression and production of defective proteins. Accordingly, thesemolecules can be used to treat a disorder, such as CHD oraneurysm/dissection, characterized by abnormal or undesired geneexpression or expression of certain defective proteins. This techniquecan involve cleavage by means of ribozymes containing nucleotidesequences complementary to one or more regions in the mRNA thatattenuate the ability of the mRNA to be translated. Possible mRNAregions include, for example, protein-coding regions and particularlyprotein-coding regions corresponding to catalytic activities,substrate/ligand binding, or other functional activities of a protein.

The SNPs of the present invention are also useful for designing RNAinterference reagents that specifically target nucleic acid moleculeshaving particular SNP variants. RNA interference (RNAi), also referredto as gene silencing, is based on using double-stranded RNA (dsRNA)molecules to turn genes off. When introduced into a cell, dsRNAs areprocessed by the cell into short fragments (generally about 21, 22, or23 nucleotides in length) known as small interfering RNAs (siRNAs) whichthe cell uses in a sequence-specific manner to recognize and destroycomplementary RNAs. Thompson, Drug Discovery Today 7(17): 912-917(2002). Accordingly, an aspect of the present invention specificallycontemplates isolated nucleic acid molecules that are about 18-26nucleotides in length, preferably 19-25 nucleotides in length, and morepreferably 20, 21, 22, or 23 nucleotides in length, and the use of thesenucleic acid molecules for RNAi. Because RNAi molecules, includingsiRNAs, act in a sequence-specific manner, the SNPs of the presentinvention can be used to design RNAi reagents that recognize and destroynucleic acid molecules having specific SNP alleles/nucleotides (such asdeleterious alleles that lead to the production of defective proteins),while not affecting nucleic acid molecules having alternative SNPalleles (such as alleles that encode proteins having normal function).As with antisense reagents, RNAi reagents may be directly useful astherapeutic agents (e.g., for turning off defective, disease-causinggenes), and are also useful for characterizing and validating genefunction (e.g., in gene knock-out or knock-down experiments).

The following references provide a further review of RNAi: Reynolds etal., “Rational siRNA design for RNA interference,” Nat Biotechnol22(3):326-30 (March 2004); Epub Feb. 1, 2004; Chi et al., “Genomewideview of gene silencing by small interfering RNAs,” PNAS100(11):6343-6346 (2003); Vickers et al., “Efficient Reduction of TargetRNAs by Small Interfering RNA and RNase H-dependent Antisense Agents,” JBiol Chem 278:7108-7118 (2003); Agami, “RNAi and related mechanisms andtheir potential use for therapy,” Curr Opin Chem Biol 6(6):829-34(December 2002); Lavery et al., “Antisense and RNAi: powerful tools indrug target discovery and validation,” Curr Opin Drug Discov Devel6(4):561-9 (July 2003); Shi, “Mammalian RNAi for the masses,” TrendsGenet 19(1):9-12 (January 2003); Shuey et al., “RNAi: gene-silencing intherapeutic intervention,” Drug Discovery Today 7(20): 1040-1046(October 2002); McManus et al., Nat Rev Genet 3(10):737-47 (October2002); Xia et al., Nat Biotechnol 20(10):1006-10 (October 2002);Plasterk et al., Curr Opin Genet Dev 10(5):562-7 (October 2000); Bosheret al., Nat Cell Biol 2(2): E31-6 (February 2000); and Hunter, Curr Biol17; 9(12):R440-2 (June 1999).

A subject suffering from a pathological condition ascribed to a SNP,such as CHD or aneurysm/dissection, may be treated so as to correct thegenetic defect. See Kren et al., Proc Natl Acad Sci USA 96:10349-10354(1999). Such a subject can be identified by any method that can detectthe polymorphism in a biological sample drawn from the subject. Such agenetic defect may be permanently corrected by administering to such asubject a nucleic acid fragment incorporating a repair sequence thatsupplies the normal/wild-type nucleotide at the position of the SNP.This site-specific repair sequence can encompass an RNA/DNAoligonucleotide that operates to promote endogenous repair of asubject's genomic DNA. The site-specific repair sequence is administeredin an appropriate vehicle, such as a complex with polyethylenimine,encapsulated in anionic liposomes, a viral vector such as an adenovirus,or other pharmaceutical composition that promotes intracellular uptakeof the administered nucleic acid. A genetic defect leading to an inbornpathology may then be overcome, as the chimeric oligonucleotides induceincorporation of the normal sequence into the subject's genome. Uponincorporation, the normal gene product is expressed, and the replacementis propagated, thereby engendering a permanent repair and therapeuticenhancement of the clinical condition of the subject.

In cases in which a cSNP results in a variant protein that is ascribedto be the cause of, or a contributing factor to, a pathologicalcondition, a method of treating such a condition can includeadministering to a subject experiencing the pathology thewild-type/normal cognate of the variant protein. Once administered in aneffective dosing regimen, the wild-type cognate provides complementationor remediation of the pathological condition.

The invention further provides a method for identifying a compound oragent that can be used to treat CHD or aneurysm/dissection. The SNPsdisclosed herein are useful as targets for the identification and/ordevelopment of therapeutic agents. A method for identifying atherapeutic agent or compound typically includes assaying the ability ofthe agent or compound to modulate the activity and/or expression of aSNP-containing nucleic acid or the encoded product and thus identifyingan agent or a compound that can be used to treat a disordercharacterized by undesired activity or expression of the SNP-containingnucleic acid or the encoded product. The assays can be performed incell-based and cell-free systems. Cell-based assays can include cellsnaturally expressing the nucleic acid molecules of interest orrecombinant cells genetically engineered to express certain nucleic acidmolecules.

Variant gene expression in a CHD or aneurysm/dissection patient caninclude, for example, either expression of a SNP-containing nucleic acidsequence (for instance, a gene that contains a SNP can be transcribedinto an mRNA transcript molecule containing the SNP, which can in turnbe translated into a variant protein) or altered expression of anormal/wild-type nucleic acid sequence due to one or more SNPs (forinstance, a regulatory/control region can contain a SNP that affects thelevel or pattern of expression of a normal transcript).

Assays for variant gene expression can involve direct assays of nucleicacid levels (e.g., mRNA levels), expressed protein levels, or ofcollateral compounds involved in a signal pathway. Further, theexpression of genes that are up- or down-regulated in response to thesignal pathway can also be assayed. In this embodiment, the regulatoryregions of these genes can be operably linked to a reporter gene such asluciferase.

Modulators of variant gene expression can be identified in a methodwherein, for example, a cell is contacted with a candidatecompound/agent and the expression of mRNA determined. The level ofexpression of mRNA in the presence of the candidate compound is comparedto the level of expression of mRNA in the absence of the candidatecompound. The candidate compound can then be identified as a modulatorof variant gene expression based on this comparison and be used to treata disorder such as CHD or aneurysm/dissection that is characterized byvariant gene expression (e.g., either expression of a SNP-containingnucleic acid or altered expression of a normal/wild-type nucleic acidmolecule due to one or more SNPs that affect expression of the nucleicacid molecule) due to one or more SNPs of the present invention. Whenexpression of mRNA is statistically significantly greater in thepresence of the candidate compound than in its absence, the candidatecompound is identified as a stimulator of nucleic acid expression. Whennucleic acid expression is statistically significantly less in thepresence of the candidate compound than in its absence, the candidatecompound is identified as an inhibitor of nucleic acid expression.

The invention further provides methods of treatment, with the SNP orassociated nucleic acid domain (e.g., catalytic domain,ligand/substrate-binding domain, regulatory/control region, etc.) orgene, or the encoded mRNA transcript, as a target, using a compoundidentified through drug screening as a gene modulator to modulatevariant nucleic acid expression. Modulation can include eitherup-regulation (i.e., activation or agonization) or down-regulation(i.e., suppression or antagonization) of nucleic acid expression.

Expression of mRNA transcripts and encoded proteins, either wild type orvariant, may be altered in individuals with a particular SNP allele in aregulatory/control element, such as a promoter or transcription factorbinding domain, that regulates expression. In this situation, methods oftreatment and compounds can be identified, as discussed herein, thatregulate or overcome the variant regulatory/control element, therebygenerating normal, or healthy, expression levels of either the wild typeor variant protein.

The SNP-containing nucleic acid molecules of the present invention arealso useful for monitoring the effectiveness of modulating compounds onthe expression or activity of a variant gene, or encoded product, inclinical trials or in a treatment regimen. Thus, the gene expressionpattern can serve as an indicator for the continuing effectiveness oftreatment with the compound, particularly with compounds to which apatient can develop resistance, as well as an indicator for toxicities.The gene expression pattern can also serve as a marker indicative of aphysiological response of the affected cells to the compound.Accordingly, such monitoring would allow either increased administrationof the compound or the administration of alternative compounds to whichthe patient has not become resistant. Similarly, if the level of nucleicacid expression falls below a desirable level, administration of thecompound could be commensurately decreased.

In another aspect of the present invention, there is provided apharmaceutical pack comprising a therapeutic agent (e.g., a smallmolecule drug, antibody, peptide, antisense or RNAi nucleic acidmolecule, etc.) and a set of instructions for administration of thetherapeutic agent to humans diagnostically tested for one or more SNPsor SNP haplotypes provided by the present invention.

The SNPs/haplotypes of the present invention are also useful forimproving many different aspects of the drug development process. Forinstance, an aspect of the present invention includes selectingindividuals for clinical trials based on their SNP genotype. Forexample, individuals with SNP genotypes that indicate that they arelikely to positively respond to a drug can be included in the trials,whereas those individuals whose SNP genotypes indicate that they areless likely to or would not respond to the drug, or who are at risk forsuffering toxic effects or other adverse reactions, can be excluded fromthe clinical trials. This not only can improve the safety of clinicaltrials, but also can enhance the chances that the trial will demonstratestatistically significant efficacy. Furthermore, the SNPs of the presentinvention may explain why certain previously developed drugs performedpoorly in clinical trials and may help identify a subset of thepopulation that would benefit from a drug that had previously performedpoorly in clinical trials, thereby “rescuing” previously developeddrugs, and enabling the drug to be made available to a particular CHD oraneurysm/dissection patient population that can benefit from it.

SNPs have many important uses in drug discovery, screening, anddevelopment. A high probability exists that, for any gene/proteinselected as a potential drug target, variants of that gene/protein willexist in a patient population. Thus, determining the impact ofgene/protein variants on the selection and delivery of a therapeuticagent should be an integral aspect of the drug discovery and developmentprocess. Jazwinska, A Trends Guide to Genetic Variation and GenomicMedicine S30-S36 (March 2002).

Knowledge of variants (e.g., SNPs and any corresponding amino acidpolymorphisms) of a particular therapeutic target (e.g., a gene, mRNAtranscript, or protein) enables parallel screening of the variants inorder to identify therapeutic candidates (e.g., small moleculecompounds, antibodies, antisense or RNAi nucleic acid compounds, etc.)that demonstrate efficacy across variants. Rothberg, Nat Biotechnol19(3):209-11 (March 2001). Such therapeutic candidates would be expectedto show equal efficacy across a larger segment of the patientpopulation, thereby leading to a larger potential market for thetherapeutic candidate.

Furthermore, identifying variants of a potential therapeutic targetenables the most common form of the target to be used for selection oftherapeutic candidates, thereby helping to ensure that the experimentalactivity that is observed for the selected candidates reflects the realactivity expected in the largest proportion of a patient population.Jazwinska, A Trends Guide to Genetic Variation and Genomic MedicineS30-S36 (March 2002).

Additionally, screening therapeutic candidates against all knownvariants of a target can enable the early identification of potentialtoxicities and adverse reactions relating to particular variants. Forexample, variability in drug absorption, distribution, metabolism andexcretion (ADME) caused by, for example, SNPs in therapeutic targets ordrug metabolizing genes, can be identified, and this information can beutilized during the drug development process to minimize variability indrug disposition and develop therapeutic agents that are safer across awider range of a patient population. The SNPs of the present invention,including the variant proteins and encoding polymorphic nucleic acidmolecules provided in Tables 1 and 2, are useful in conjunction with avariety of toxicology methods established in the art, such as those setforth in Current Protocols in Toxicology, John Wiley & Sons, Inc., N.Y.

Furthermore, therapeutic agents that target any art-known proteins (ornucleic acid molecules, either RNA or DNA) may cross-react with thevariant proteins (or polymorphic nucleic acid molecules) disclosed inTable 1, thereby significantly affecting the pharmacokinetic propertiesof the drug. Consequently, the protein variants and the SNP-containingnucleic acid molecules disclosed in Tables 1 and 2 are useful indeveloping, screening, and evaluating therapeutic agents that targetcorresponding art-known protein forms (or nucleic acid molecules).Additionally, as discussed above, knowledge of all polymorphic forms ofa particular drug target enables the design of therapeutic agents thatare effective against most or all such polymorphic forms of the drugtarget.

Pharmaceutical Compositions and Administration Thereof

Any of the CHD, aneurysm/dissection, and/or statin response-associatedproteins, and encoding nucleic acid molecules, disclosed herein can beused as therapeutic targets (or directly used themselves as therapeuticcompounds) for treating or preventing CHD, aneurysm/dissection, orrelated pathologies, and the present disclosure enables therapeuticcompounds (e.g., small molecules, antibodies, therapeutic proteins, RNAiand antisense molecules, etc.) to be developed that target (or arecomprised of) any of these therapeutic targets.

In general, a therapeutic compound will be administered in atherapeutically effective amount by any of the accepted modes ofadministration for agents that serve similar utilities. The actualamount of the therapeutic compound of this invention, i.e., the activeingredient, will depend upon numerous factors such as the severity ofthe disease to be treated, the age and relative health of the subject,the potency of the compound used, the route and form of administration,and other factors.

Therapeutically effective amounts of therapeutic compounds may rangefrom, for example, approximately 0.01-50 mg per kilogram body weight ofthe recipient per day; preferably about 0.1-20 mg/kg/day. Thus, as anexample, for administration to a 70-kg person, the dosage range wouldmost preferably be about 7 mg to 1.4 g per day.

In general, therapeutic compounds will be administered as pharmaceuticalcompositions by any one of the following routes: oral, systemic (e.g.,transdermal, intranasal, or by suppository), or parenteral (e.g.,intramuscular, intravenous, or subcutaneous) administration. Thepreferred manner of administration is oral or parenteral using aconvenient daily dosage regimen, which can be adjusted according to thedegree of affliction. Oral compositions can take the form of tablets,pills, capsules, semisolids, powders, sustained release formulations,solutions, suspensions, elixirs, aerosols, or any other appropriatecompositions.

The choice of formulation depends on various factors such as the mode ofdrug administration (e.g., for oral administration, formulations in theform of tablets, pills, or capsules are preferred) and thebioavailability of the drug substance. Recently, pharmaceuticalformulations have been developed especially for drugs that show poorbioavailability based upon the principle that bioavailability can beincreased by increasing the surface area, i.e., decreasing particlesize. For example, U.S. Pat. No. 4,107,288 describes a pharmaceuticalformulation having particles in the size range from 10 to 1,000 nm inwhich the active material is supported on a cross-linked matrix ofmacromolecules. U.S. Pat. No. 5,145,684 describes the production of apharmaceutical formulation in which the drug substance is pulverized tonanoparticles (average particle size of 400 nm) in the presence of asurface modifier and then dispersed in a liquid medium to give apharmaceutical formulation that exhibits remarkably highbioavailability.

Pharmaceutical compositions are comprised of, in general, a therapeuticcompound in combination with at least one pharmaceutically acceptableexcipient. Acceptable excipients are non-toxic, aid administration, anddo not adversely affect the therapeutic benefit of the therapeuticcompound. Such excipients may be any solid, liquid, semi-solid or, inthe case of an aerosol composition, gaseous excipient that is generallyavailable to one skilled in the art.

Solid pharmaceutical excipients include starch, cellulose, talc,glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silicagel, magnesium stearate, sodium stearate, glycerol monostearate, sodiumchloride, dried skim milk and the like. Liquid and semisolid excipientsmay be selected from glycerol, propylene glycol, water, ethanol andvarious oils, including those of petroleum, animal, vegetable orsynthetic origin, e.g., peanut oil, soybean oil, mineral oil, sesameoil, etc. Preferred liquid carriers, particularly for injectablesolutions, include water, saline, aqueous dextrose, and glycols.

Compressed gases may be used to disperse a compound of this invention inaerosol form. Inert gases suitable for this purpose are nitrogen, carbondioxide, etc.

Other suitable pharmaceutical excipients and their formulations aredescribed in Remington's Pharmaceutical Sciences 18^(th) ed., E. W.Martin, ed., Mack Publishing Company (1990).

The amount of the therapeutic compound in a formulation can vary withinthe full range employed by those skilled in the art. Typically, theformulation will contain, on a weight percent (wt %) basis, from about0.01-99.99 wt % of the therapeutic compound based on the totalformulation, with the balance being one or more suitable pharmaceuticalexcipients. Preferably, the compound is present at a level of about1-80% wt.

Therapeutic compounds can be administered alone or in combination withother therapeutic compounds or in combination with one or more otheractive ingredient(s). For example, an inhibitor or stimulator of a CHDor aneurysm/dissection-associated protein can be administered incombination with another agent that inhibits or stimulates the activityof the same or a different CHD or aneurysm/dissection-associated proteinto thereby counteract the effects of CHD or aneurysm/dissection.

For further information regarding pharmacology, see Current Protocols inPharmacology, John Wiley & Sons, Inc., N.Y.

Human Identification Applications

In addition to their diagnostic, therapeutic, and preventive uses inCHD, aneurysm/dissection, and related pathologies, as well as inpredicting response to drug treatment, particularly statin treatment,the SNPs provided by the present invention are also useful as humanidentification markers for such applications as forensics, paternitytesting, and biometrics. See, e.g., Gill, “An assessment of the utilityof single nucleotide polymorphisms (SNPs) for forensic purposes,” Int JLegal Med 114(4-5):204-10 (2001). Genetic variations in the nucleic acidsequences between individuals can be used as genetic markers to identifyindividuals and to associate a biological sample with an individual.Determination of which nucleotides occupy a set of SNP positions in anindividual identifies a set of SNP markers that distinguishes theindividual. The more SNP positions that are analyzed, the lower theprobability that the set of SNPs in one individual is the same as thatin an unrelated individual. Preferably, if multiple sites are analyzed,the sites are unlinked (i.e., inherited independently). Thus, preferredsets of SNPs can be selected from among the SNPs disclosed herein, whichmay include SNPs on different chromosomes, SNPs on different chromosomearms, and/or SNPs that are dispersed over substantial distances alongthe same chromosome arm.

Furthermore, among the SNPs disclosed herein, preferred SNPs for use incertain forensic/human identification applications include SNPs locatedat degenerate codon positions (i.e., the third position in certaincodons which can be one of two or more alternative nucleotides and stillencode the same amino acid), since these SNPs do not affect the encodedprotein. SNPs that do not affect the encoded protein are expected to beunder less selective pressure and are therefore expected to be morepolymorphic in a population, which is typically an advantage forforensic/human identification applications. However, for certainforensics/human identification applications, such as predictingphenotypic characteristics (e.g., inferring ancestry or inferring one ormore physical characteristics of an individual) from a DNA sample, itmay be desirable to utilize SNPs that affect the encoded protein.

For many of the SNPs disclosed in Tables 1 and 2 (which are identifiedas “Applera” SNP source), Tables 1 and 2 provide SNP allele frequenciesobtained by re-sequencing the DNA of chromosomes from 39 individuals(Tables 1 and 2 also provide allele frequency information for “Celera”source SNPs and, where available, public SNPs from dbEST, HGBASE, and/orHGMD). The allele frequencies provided in Tables 1 and 2 enable theseSNPs to be readily used for human identification applications. Althoughany SNP disclosed in Table 1 and/or Table 2 could be used for humanidentification, the closer that the frequency of the minor allele at aparticular SNP site is to 50%, the greater the ability of that SNP todiscriminate between different individuals in a population since itbecomes increasingly likely that two randomly selected individuals wouldhave different alleles at that SNP site. Using the SNP allelefrequencies provided in Tables 1 and 2, one of ordinary skill in the artcould readily select a subset of SNPs for which the frequency of theminor allele is, for example, at least 1%, 2%, 5%, 10%, 20%, 25%, 30%,40%, 45%, or 50%, or any other frequency in-between. Thus, since Tables1 and 2 provide allele frequencies based on the re-sequencing of thechromosomes from 39 individuals, a subset of SNPs could readily beselected for human identification in which the total allele count of theminor allele at a particular SNP site is, for example, at least 1, 2, 4,8, 10, 16, 20, 24, 30, 32, 36, 38, 39, 40, or any other numberin-between.

Furthermore, Tables 1 and 2 also provide population group(interchangeably referred to herein as ethnic or racial groups)information coupled with the extensive allele frequency information. Forexample, the group of 39 individuals whose DNA was re-sequenced wasmade-up of 20 Caucasians and 19 African-Americans. This population groupinformation enables further refinement of SNP selection for humanidentification. For example, preferred SNPs for human identification canbe selected from Tables 1 and 2 that have similar allele frequencies inboth the Caucasian and African-American populations; thus, for example,SNPs can be selected that have equally high discriminatory power in bothpopulations. Alternatively, SNPs can be selected for which there is astatistically significant difference in allele frequencies between theCaucasian and African-American populations (as an extreme example, aparticular allele may be observed only in either the Caucasian or theAfrican-American population group but not observed in the otherpopulation group); such SNPs are useful, for example, for predicting therace/ethnicity of an unknown perpetrator from a biological sample suchas a hair or blood stain recovered at a crime scene. For a discussion ofusing SNPs to predict ancestry from a DNA sample, including statisticalmethods, see Frudakis et al., “A Classifier for the SNP-Based Inferenceof Ancestry,” Journal of Forensic Sciences 48(4):771-782 (2003).

SNPs have numerous advantages over other types of polymorphic markers,such as short tandem repeats (STRs). For example, SNPs can be easilyscored and are amenable to automation, making SNPs the markers of choicefor large-scale forensic databases. SNPs are found in much greaterabundance throughout the genome than repeat polymorphisms. Populationfrequencies of two polymorphic forms can usually be determined withgreater accuracy than those of multiple polymorphic forms atmulti-allelic loci. SNPs are mutationally more stable than repeatpolymorphisms. SNPs are not susceptible to artifacts such as stutterbands that can hinder analysis. Stutter bands are frequently encounteredwhen analyzing repeat polymorphisms, and are particularly troublesomewhen analyzing samples such as crime scene samples that may containmixtures of DNA from multiple sources. Another significant advantage ofSNP markers over STR markers is the much shorter length of nucleic acidneeded to score a SNP. For example, STR markers are generally severalhundred base pairs in length. A SNP, on the other hand, comprises asingle nucleotide, and generally a short conserved region on either sideof the SNP position for primer and/or probe binding. This makes SNPsmore amenable to typing in highly degraded or aged biological samplesthat are frequently encountered in forensic casework in which DNA may befragmented into short pieces.

SNPs also are not subject to microvariant and “off-ladder” allelesfrequently encountered when analyzing STR loci. Microvariants aredeletions or insertions within a repeat unit that change the size of theamplified DNA product so that the amplified product does not migrate atthe same rate as reference alleles with normal sized repeat units. Whenseparated by size, such as by electrophoresis on a polyacrylamide gel,microvariants do not align with a reference allelic ladder of standardsized repeat units, but rather migrate between the reference alleles.The reference allelic ladder is used for precise sizing of alleles forallele classification; therefore alleles that do not align with thereference allelic ladder lead to substantial analysis problems.Furthermore, when analyzing multi-allelic repeat polymorphisms,occasionally an allele is found that consists of more or less repeatunits than has been previously seen in the population, or more or lessrepeat alleles than are included in a reference allelic ladder. Thesealleles will migrate outside the size range of known alleles in areference allelic ladder, and therefore are referred to as “off-ladder”alleles. In extreme cases, the allele may contain so few or so manyrepeats that it migrates well out of the range of the reference allelicladder. In this situation, the allele may not even be observed, or, withmultiplex analysis, it may migrate within or close to the size range foranother locus, further confounding analysis.

SNP analysis avoids the problems of microvariants and off-ladder allelesencountered in STR analysis. Importantly, microvariants and off-ladderalleles may provide significant problems, and may be completely missed,when using analysis methods such as oligonucleotide hybridizationarrays, which utilize oligonucleotide probes specific for certain knownalleles. Furthermore, off-ladder alleles and microvariants encounteredwith STR analysis, even when correctly typed, may lead to improperstatistical analysis, since their frequencies in the population aregenerally unknown or poorly characterized, and therefore the statisticalsignificance of a matching genotype may be questionable. All theseadvantages of SNP analysis are considerable in light of the consequencesof most DNA identification cases, which may lead to life imprisonmentfor an individual, or re-association of remains to the family of adeceased individual.

DNA can be isolated from biological samples such as blood, bone, hair,saliva, or semen, and compared with the DNA from a reference source atparticular SNP positions. Multiple SNP markers can be assayedsimultaneously in order to increase the power of discrimination and thestatistical significance of a matching genotype. For example,oligonucleotide arrays can be used to genotype a large number of SNPssimultaneously. The SNPs provided by the present invention can beassayed in combination with other polymorphic genetic markers, such asother SNPs known in the art or STRs, in order to identify an individualor to associate an individual with a particular biological sample.

Furthermore, the SNPs provided by the present invention can be genotypedfor inclusion in a database of DNA genotypes, for example, a criminalDNA databank such as the FBI's Combined DNA Index System (CODIS)database. A genotype obtained from a biological sample of unknown sourcecan then be queried against the database to find a matching genotype,with the SNPs of the present invention providing nucleotide positions atwhich to compare the known and unknown DNA sequences for identity.Accordingly, the present invention provides a database comprising novelSNPs or SNP alleles of the present invention (e.g., the database cancomprise information indicating which alleles are possessed byindividual members of a population at one or more novel SNP sites of thepresent invention), such as for use in forensics, biometrics, or otherhuman identification applications. Such a database typically comprises acomputer-based system in which the SNPs or SNP alleles of the presentinvention are recorded on a computer readable medium.

The SNPs of the present invention can also be assayed for use inpaternity testing. The object of paternity testing is usually todetermine whether a male is the father of a child. In most cases, themother of the child is known and thus, the mother's contribution to thechild's genotype can be traced. Paternity testing investigates whetherthe part of the child's genotype not attributable to the mother isconsistent with that of the putative father. Paternity testing can beperformed by analyzing sets of polymorphisms in the putative father andthe child, with the SNPs of the present invention providing nucleotidepositions at which to compare the putative father's and child's DNAsequences for identity. If the set of polymorphisms in the childattributable to the father does not match the set of polymorphisms ofthe putative father, it can be concluded, barring experimental error,that the putative father is not the father of the child. If the set ofpolymorphisms in the child attributable to the father match the set ofpolymorphisms of the putative father, a statistical calculation can beperformed to determine the probability of coincidental match, and aconclusion drawn as to the likelihood that the putative father is thetrue biological father of the child.

In addition to paternity testing, SNPs are also useful for other typesof kinship testing, such as for verifying familial relationships forimmigration purposes, or for cases in which an individual alleges to berelated to a deceased individual in order to claim an inheritance fromthe deceased individual, etc. For further information regarding theutility of SNPs for paternity testing and other types of kinshiptesting, including methods for statistical analysis, see Krawczak,“Informativity assessment for biallelic single nucleotidepolymorphisms,” Electrophoresis 20(8):1676-81 (June 1999).

The use of the SNPs of the present invention for human identificationfurther extends to various authentication systems, commonly referred toas biometric systems, which typically convert physical characteristicsof humans (or other organisms) into digital data. Biometric systemsinclude various technological devices that measure such uniqueanatomical or physiological characteristics as finger, thumb, or palmprints; hand geometry; vein patterning on the back of the hand; bloodvessel patterning of the retina and color and texture of the iris;facial characteristics; voice patterns; signature and typing dynamics;and DNA. Such physiological measurements can be used to verify identityand, for example, restrict or allow access based on the identification.Examples of applications for biometrics include physical area security,computer and network security, aircraft passenger check-in and boarding,financial transactions, medical records access, government benefitdistribution, voting, law enforcement, passports, visas and immigration,prisons, various military applications, and for restricting access toexpensive or dangerous items, such as automobiles or guns. See, forexample, O'Connor, Stanford Technology Law Review, and U.S. Pat. No.6,119,096.

Groups of SNPs, particularly the SNPs provided by the present invention,can be typed to uniquely identify an individual for biometricapplications such as those described above. Such SNP typing can readilybe accomplished using, for example, DNA chips/arrays. Preferably, aminimally invasive means for obtaining a DNA sample is utilized. Forexample, PCR amplification enables sufficient quantities of DNA foranalysis to be obtained from buccal swabs or fingerprints, which containDNA-containing skin cells and oils that are naturally transferred duringcontact.

Further information regarding techniques for using SNPs inforensic/human identification applications can be found, for example, inCurrent Protocols in Human Genetics 14.1-14.7, John Wiley & Sons, N.Y.(2002).

Variant Proteins, Antibodies, Vectors, Host Cells, & Uses Thereof

Variant Proteins Encoded by SNP-Containing Nucleic Acid Molecules

The present invention provides SNP-containing nucleic acid molecules,many of which encode proteins having variant amino acid sequences ascompared to the art-known (i.e., wild-type) proteins. Amino acidsequences encoded by the polymorphic nucleic acid molecules of thepresent invention are referred to as SEQ ID NO:2 in Table 1 and providedin the Sequence Listing. These variants will generally be referred toherein as variant proteins/peptides/polypeptides, or polymorphicproteins/peptides/polypeptides of the present invention. The terms“protein,” “peptide,” and “polypeptide” are used herein interchangeably.

A variant protein of the present invention may be encoded by, forexample, a nonsynonymous nucleotide substitution at any one of the cSNPpositions disclosed herein. In addition, variant proteins may alsoinclude proteins whose expression, structure, and/or function is alteredby a SNP disclosed herein, such as a SNP that creates or destroys a stopcodon, a SNP that affects splicing, and a SNP in control/regulatoryelements, e.g. promoters, enhancers, or transcription factor bindingdomains.

As used herein, a protein or peptide is said to be “isolated” or“purified” when it is substantially free of cellular material orchemical precursors or other chemicals. The variant proteins of thepresent invention can be purified to homogeneity or other lower degreesof purity. The level of purification will be based on the intended use.The key feature is that the preparation allows for the desired functionof the variant protein, even if in the presence of considerable amountsof other components.

As used herein, “substantially free of cellular material” includespreparations of the variant protein having less than about 30% (by dryweight) other proteins (i.e., contaminating protein), less than about20% other proteins, less than about 10% other proteins, or less thanabout 5% other proteins. When the variant protein is recombinantlyproduced, it can also be substantially free of culture medium, i.e.,culture medium represents less than about 20% of the volume of theprotein preparation.

The language “substantially free of chemical precursors or otherchemicals” includes preparations of the variant protein in which it isseparated from chemical precursors or other chemicals that are involvedin its synthesis. In one embodiment, the language “substantially free ofchemical precursors or other chemicals” includes preparations of thevariant protein having less than about 30% (by dry weight) chemicalprecursors or other chemicals, less than about 20% chemical precursorsor other chemicals, less than about 10% chemical precursors or otherchemicals, or less than about 5% chemical precursors or other chemicals.

An isolated variant protein may be purified from cells that naturallyexpress it, purified from cells that have been altered to express it(recombinant host cells), or synthesized using known protein synthesismethods. For example, a nucleic acid molecule containing SNP(s) encodingthe variant protein can be cloned into an expression vector, theexpression vector introduced into a host cell, and the variant proteinexpressed in the host cell. The variant protein can then be isolatedfrom the cells by any appropriate purification scheme using standardprotein purification techniques. Examples of these techniques aredescribed in detail below. Sambrook and Russell, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Laboratory Press, N.Y. (2000).

The present invention provides isolated variant proteins that comprise,consist of or consist essentially of amino acid sequences that containone or more variant amino acids encoded by one or more codons thatcontain a SNP of the present invention.

Accordingly, the present invention provides variant proteins thatconsist of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists of an amino acid sequencewhen the amino acid sequence is the entire amino acid sequence of theprotein.

The present invention further provides variant proteins that consistessentially of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists essentially of an aminoacid sequence when such an amino acid sequence is present with only afew additional amino acid residues in the final protein.

The present invention further provides variant proteins that compriseamino acid sequences that contain one or more amino acid polymorphisms(or truncations or extensions due to creation or destruction of a stopcodon, respectively) encoded by the SNPs provided in Table 1 and/orTable 2. A protein comprises an amino acid sequence when the amino acidsequence is at least part of the final amino acid sequence of theprotein. In such a fashion, the protein may contain only the variantamino acid sequence or have additional amino acid residues, such as acontiguous encoded sequence that is naturally associated with it orheterologous amino acid residues. Such a protein can have a fewadditional amino acid residues or can comprise many more additionalamino acids. A brief description of how various types of these proteinscan be made and isolated is provided below.

The variant proteins of the present invention can be attached toheterologous sequences to form chimeric or fusion proteins. Suchchimeric and fusion proteins comprise a variant protein operativelylinked to a heterologous protein having an amino acid sequence notsubstantially homologous to the variant protein. “Operatively linked”indicates that the coding sequences for the variant protein and theheterologous protein are ligated in-frame. The heterologous protein canbe fused to the N-terminus or C-terminus of the variant protein. Inanother embodiment, the fusion protein is encoded by a fusionpolynucleotide that is synthesized by conventional techniques includingautomated DNA synthesizers. Alternatively, PCR amplification of genefragments can be carried out using anchor primers which give rise tocomplementary overhangs between two consecutive gene fragments which cansubsequently be annealed and re-amplified to generate a chimeric genesequence. See Ausubel et al., Current Protocols in Molecular Biology(1992). Moreover, many expression vectors are commercially availablethat already encode a fusion moiety (e.g., a GST protein). A variantprotein-encoding nucleic acid can be cloned into such an expressionvector such that the fusion moiety is linked in-frame to the variantprotein.

In many uses, the fusion protein does not affect the activity of thevariant protein. The fusion protein can include, but is not limited to,enzymatic fusion proteins, for example, beta-galactosidase fusions,yeast two-hybrid GAL fusions, poly-His fusions, MYC-tagged, HI-taggedand Ig fusions. Such fusion proteins, particularly poly-His fusions, canfacilitate their purification following recombinant expression. Incertain host cells (e.g., mammalian host cells), expression and/orsecretion of a protein can be increased by using a heterologous signalsequence. Fusion proteins are further described in, for example, Terpe,“Overview of tag protein fusions: from molecular and biochemicalfundamentals to commercial systems,” Appl Microbiol Biotechnol60(5):523-33 (January 2003); Epub Nov. 7, 2002; Graddis et al.,“Designing proteins that work using recombinant technologies,” CurrPharm Biotechnol 3(4):285-97 (December 2002); and Nilsson et al.,“Affinity fusion strategies for detection, purification, andimmobilization of recombinant proteins,” Protein Expr Purif 11(1):1-16(October 1997).

The present invention also relates to further obvious variants of thevariant polypeptides of the present invention, such asnaturally-occurring mature forms (e.g., allelic variants), non-naturallyoccurring recombinantly-derived variants, and orthologs and paralogs ofsuch proteins that share sequence homology. Such variants can readily begenerated using art-known techniques in the fields of recombinantnucleic acid technology and protein biochemistry. It is understood,however, that variants exclude those known in the prior art before thepresent invention.

Further variants of the variant polypeptides disclosed in Table 1 cancomprise an amino acid sequence that shares at least 70-80%, 80-85%,85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% sequence identitywith an amino acid sequence disclosed in Table 1 (or a fragment thereof)and that includes a novel amino acid residue (allele) disclosed in Table1 (which is encoded by a novel SNP allele). Thus, an aspect of thepresent invention that is specifically contemplated are polypeptidesthat have a certain degree of sequence variation compared with thepolypeptide sequences shown in Table 1, but that contain a novel aminoacid residue (allele) encoded by a novel SNP allele disclosed herein. Inother words, as long as a polypeptide contains a novel amino acidresidue disclosed herein, other portions of the polypeptide that flankthe novel amino acid residue can vary to some degree from thepolypeptide sequences shown in Table 1.

Full-length pre-processed forms, as well as mature processed forms, ofproteins that comprise one of the amino acid sequences disclosed hereincan readily be identified as having complete sequence identity to one ofthe variant proteins of the present invention as well as being encodedby the same genetic locus as the variant proteins provided herein.

Orthologs of a variant peptide can readily be identified as having somedegree of significant sequence homology/identity to at least a portionof a variant peptide as well as being encoded by a gene from anotherorganism. Preferred orthologs will be isolated from non-human mammals,preferably primates, for the development of human therapeutic targetsand agents. Such orthologs can be encoded by a nucleic acid sequencethat hybridizes to a variant peptide-encoding nucleic acid moleculeunder moderate to stringent conditions depending on the degree ofrelatedness of the two organisms yielding the homologous proteins.

Variant proteins include, but are not limited to, proteins containingdeletions, additions and substitutions in the amino acid sequence causedby the SNPs of the present invention. One class of substitutions isconserved amino acid substitutions in which a given amino acid in apolypeptide is substituted for another amino acid of likecharacteristics. Typical conservative substitutions are replacements,one for another, among the aliphatic amino acids Ala, Val, Leu, and Ile;interchange of the hydroxyl residues Ser and Thr; exchange of the acidicresidues Asp and Glu; substitution between the amide residues Asn andGln; exchange of the basic residues Lys and Arg; and replacements amongthe aromatic residues Phe and Tyr. Guidance concerning which amino acidchanges are likely to be phenotypically silent are found, for example,in Bowie et al., Science 247:1306-1310 (1990).

Variant proteins can be fully functional or can lack function in one ormore activities, e.g. ability to bind another molecule, ability tocatalyze a substrate, ability to mediate signaling, etc. Fullyfunctional variants typically contain only conservative variations orvariations in non-critical residues or in non-critical regions.Functional variants can also contain substitution of similar amino acidsthat result in no change or an insignificant change in function.Alternatively, such substitutions may positively or negatively affectfunction to some degree. Non-functional variants typically contain oneor more non-conservative amino acid substitutions, deletions,insertions, inversions, truncations or extensions, or a substitution,insertion, inversion, or deletion of a critical residue or in a criticalregion.

Amino acids that are essential for function of a protein can beidentified by methods known in the art, such as site-directedmutagenesis or alanine-scanning mutagenesis, particularly using theamino acid sequence and polymorphism information provided in Table 1.Cunningham et al., Science 244:1081-1085 (1989). The latter procedureintroduces single alanine mutations at every residue in the molecule.The resulting mutant molecules are then tested for biological activitysuch as enzyme activity or in assays such as an in vitro proliferativeactivity. Sites that are critical for binding partner/substrate bindingcan also be determined by structural analysis such as crystallization,nuclear magnetic resonance or photoaffinity labeling. Smith et al., JMol Biol 224:899-904 (1992); de Vos et al., Science 255:306-312 (1992).

Polypeptides can contain amino acids other than the 20 amino acidscommonly referred to as the 20 naturally occurring amino acids. Further,many amino acids, including the terminal amino acids, may be modified bynatural processes, such as processing and other post-translationalmodifications, or by chemical modification techniques well known in theart. Accordingly, the variant proteins of the present invention alsoencompass derivatives or analogs in which a substituted amino acidresidue is not one encoded by the genetic code, in which a substituentgroup is included, in which the mature polypeptide is fused with anothercompound, such as a compound to increase the half-life of thepolypeptide (e.g., polyethylene glycol), or in which additional aminoacids are fused to the mature polypeptide, such as a leader or secretorysequence or a sequence for purification of the mature polypeptide or apro-protein sequence.

Known protein modifications include, but are not limited to,acetylation, acylation, ADP-ribosylation, amidation, covalent attachmentof flavin, covalent attachment of a heme moiety, covalent attachment ofa nucleotide or nucleotide derivative, covalent attachment of a lipid orlipid derivative, covalent attachment of phosphotidylinositol,cross-linking, cyclization, disulfide bond formation, demethylation,formation of covalent crosslinks, formation of cystine, formation ofpyroglutamate, formylation, gamma carboxylation, glycosylation, GPIanchor formation, hydroxylation, iodination, methylation,myristoylation, oxidation, proteolytic processing, phosphorylation,prenylation, racemization, selenoylation, sulfation, transfer-RNAmediated addition of amino acids to proteins such as arginylation, andubiquitination.

Such protein modifications are well known to those of skill in the artand have been described in great detail in the scientific literature.Particularly common modifications, for example glycosylation, lipidattachment, sulfation, gamma-carboxylation of glutamic acid residues,hydroxylation and ADP-ribosylation, are described in most basic texts,such as Proteins—Structure and Molecular Properties 2nd Ed., T. E.Creighton, W.H. Freeman and Company, N.Y. (1993); F. Wold,Posttranslational Covalent Modification of Proteins 1-12, B. C. Johnson,ed., Academic Press, N.Y. (1983); Seifter et al., Meth Enzymol182:626-646 (1990); and Rattan et al., Ann NY Acad Sci 663:48-62 (1992).

The present invention further provides fragments of the variant proteinsin which the fragments contain one or more amino acid sequencevariations (e.g., substitutions, or truncations or extensions due tocreation or destruction of a stop codon) encoded by one or more SNPsdisclosed herein. The fragments to which the invention pertains,however, are not to be construed as encompassing fragments that havebeen disclosed in the prior art before the present invention.

As used herein, a fragment may comprise at least about 4, 8, 10, 12, 14,16, 18, 20, 25, 30, 50, 100 (or any other number in-between) or morecontiguous amino acid residues from a variant protein, wherein at leastone amino acid residue is affected by a SNP of the present invention,e.g., a variant amino acid residue encoded by a nonsynonymous nucleotidesubstitution at a cSNP position provided by the present invention. Thevariant amino acid encoded by a cSNP may occupy any residue positionalong the sequence of the fragment. Such fragments can be chosen basedon the ability to retain one or more of the biological activities of thevariant protein or the ability to perform a function, e.g., act as animmunogen. Particularly important fragments are biologically activefragments. Such fragments will typically comprise a domain or motif of avariant protein of the present invention, e.g., active site,transmembrane domain, or ligand/substrate binding domain. Otherfragments include, but are not limited to, domain or motif-containingfragments, soluble peptide fragments, and fragments containingimmunogenic structures. Predicted domains and functional sites arereadily identifiable by computer programs well known to those of skillin the art (e.g., PROSITE analysis). Current Protocols in ProteinScience, John Wiley & Sons, N.Y. (2002).

Uses of Variant Proteins

The variant proteins of the present invention can be used in a varietyof ways, including but not limited to, in assays to determine thebiological activity of a variant protein, such as in a panel of multipleproteins for high-throughput screening; to raise antibodies or to elicitanother type of immune response; as a reagent (including the labeledreagent) in assays designed to quantitatively determine levels of thevariant protein (or its binding partner) in biological fluids; as amarker for cells or tissues in which it is preferentially expressed(either constitutively or at a particular stage of tissuedifferentiation or development or in a disease state); as a target forscreening for a therapeutic agent; and as a direct therapeutic agent tobe administered into a human subject. Any of the variant proteinsdisclosed herein may be developed into reagent grade or kit format forcommercialization as research products. Methods for performing the useslisted above are well known to those skilled in the art. See, e.g.,Molecular Cloning: A Laboratory Manual, Sambrook and Russell, ColdSpring Harbor Laboratory Press, N.Y. (2000), and Methods in Enzymology:Guide to Molecular Cloning Techniques, S. L. Berger and A. R. Kimmel,eds., Academic Press (1987).

In a specific embodiment of the invention, the methods of the presentinvention include detection of one or more variant proteins disclosedherein. Variant proteins are disclosed in Table 1 and in the SequenceListing as a#1-a#1. Detection of such proteins can be accomplishedusing, for example, antibodies, small molecule compounds, aptamers,ligands/substrates, other proteins or protein fragments, or otherprotein-binding agents. Preferably, protein detection agents arespecific for a variant protein of the present invention and cantherefore discriminate between a variant protein of the presentinvention and the wild-type protein or another variant form. This cangenerally be accomplished by, for example, selecting or designingdetection agents that bind to the region of a protein that differsbetween the variant and wild-type protein, such as a region of a proteinthat contains one or more amino acid substitutions that is/are encodedby a non-synonymous cSNP of the present invention, or a region of aprotein that follows a nonsense mutation-type SNP that creates a stopcodon thereby leading to a shorter polypeptide, or a region of a proteinthat follows a read-through mutation-type SNP that destroys a stop codonthereby leading to a longer polypeptide in which a portion of thepolypeptide is present in one version of the polypeptide but not theother.

In another specific aspect of the invention, the variant proteins of thepresent invention are used as targets for diagnosing CHD oraneurysm/dissection or for determining predisposition to CHD oraneurysm/dissection in a human, for treating and/or preventing CHD oraneurysm/dissection, or for predicting an individual's response tostatin treatment (particularly treatment or prevention of CHD oraneurysm/dissection using statins), etc. Accordingly, the inventionprovides methods for detecting the presence of, or levels of, one ormore variant proteins of the present invention in a cell, tissue, ororganism. Such methods typically involve contacting a test sample withan agent (e.g., an antibody, small molecule compound, or peptide)capable of interacting with the variant protein such that specificbinding of the agent to the variant protein can be detected. Such anassay can be provided in a single detection format or a multi-detectionformat such as an array, for example, an antibody or aptamer array(arrays for protein detection may also be referred to as “proteinchips”). The variant protein of interest can be isolated from a testsample and assayed for the presence of a variant amino acid sequenceencoded by one or more SNPs disclosed by the present invention. The SNPsmay cause changes to the protein and the corresponding proteinfunction/activity, such as through non-synonymous substitutions inprotein coding regions that can lead to amino acid substitutions,deletions, insertions, and/or rearrangements; formation or destructionof stop codons; or alteration of control elements such as promoters.SNPs may also cause inappropriate post-translational modifications.

One preferred agent for detecting a variant protein in a sample is anantibody capable of selectively binding to a variant form of the protein(antibodies are described in greater detail in the next section). Suchsamples include, for example, tissues, cells, and biological fluidsisolated from a subject, as well as tissues, cells and fluids presentwithin a subject.

In vitro methods for detection of the variant proteins associated withCHD or aneurysm/dissection that are disclosed herein and fragmentsthereof include, but are not limited to, enzyme linked immunosorbentassays (ELISAs), radioimmunoassays (RIA), Western blots,immunoprecipitations, immunofluorescence, and protein arrays/chips(e.g., arrays of antibodies or aptamers). For further informationregarding immunoassays and related protein detection methods, seeCurrent Protocols in Immunology, John Wiley & Sons, N.Y., and Hage,“Immunoassays,” Anal Chem 15; 71(12):294R-304R (June 1999).

Additional analytic methods of detecting amino acid variants include,but are not limited to, altered electrophoretic mobility, alteredtryptic peptide digest, altered protein activity in cell-based orcell-free assay, alteration in ligand or antibody-binding pattern,altered isoelectric point, and direct amino acid sequencing.

Alternatively, variant proteins can be detected in vivo in a subject byintroducing into the subject a labeled antibody (or other type ofdetection reagent) specific for a variant protein. For example, theantibody can be labeled with a radioactive marker whose presence andlocation in a subject can be detected by standard imaging techniques.

Other uses of the variant peptides of the present invention are based onthe class or action of the protein. For example, proteins isolated fromhumans and their mammalian orthologs serve as targets for identifyingagents (e.g., small molecule drugs or antibodies) for use in therapeuticapplications, particularly for modulating a biological or pathologicalresponse in a cell or tissue that expresses the protein. Pharmaceuticalagents can be developed that modulate protein activity.

As an alternative to modulating gene expression, therapeutic compoundscan be developed that modulate protein function. For example, many SNPsdisclosed herein affect the amino acid sequence of the encoded protein(e.g., non-synonymous cSNPs and nonsense mutation-type SNPs). Suchalterations in the encoded amino acid sequence may affect proteinfunction, particularly if such amino acid sequence variations occur infunctional protein domains, such as catalytic domains, ATP-bindingdomains, or ligand/substrate binding domains. It is well established inthe art that variant proteins having amino acid sequence variations infunctional domains can cause or influence pathological conditions. Insuch instances, compounds (e.g., small molecule drugs or antibodies) canbe developed that target the variant protein and modulate (e.g., up- ordown-regulate) protein function/activity.

The therapeutic methods of the present invention further include methodsthat target one or more variant proteins of the present invention.Variant proteins can be targeted using, for example, small moleculecompounds, antibodies, aptamers, ligands/substrates, other proteins, orother protein-binding agents. Additionally, the skilled artisan willrecognize that the novel protein variants (and polymorphic nucleic acidmolecules) disclosed in Table 1 may themselves be directly used astherapeutic agents by acting as competitive inhibitors of correspondingart-known proteins (or nucleic acid molecules such as mRNA molecules).

The variant proteins of the present invention are particularly useful indrug screening assays, in cell-based or cell-free systems. Cell-basedsystems can utilize cells that naturally express the protein, a biopsyspecimen, or cell cultures. In one embodiment, cell-based assays involverecombinant host cells expressing the variant protein. Cell-free assayscan be used to detect the ability of a compound to directly bind to avariant protein or to the corresponding SNP-containing nucleic acidfragment that encodes the variant protein.

A variant protein of the present invention, as well as appropriatefragments thereof, can be used in high-throughput screening assays totest candidate compounds for the ability to bind and/or modulate theactivity of the variant protein. These candidate compounds can befurther screened against a protein having normal function (e.g., awild-type/non-variant protein) to further determine the effect of thecompound on the protein activity. Furthermore, these compounds can betested in animal or invertebrate systems to determine in vivoactivity/effectiveness. Compounds can be identified that activate(agonists) or inactivate (antagonists) the variant protein, anddifferent compounds can be identified that cause various degrees ofactivation or inactivation of the variant protein.

Further, the variant proteins can be used to screen a compound for theability to stimulate or inhibit interaction between the variant proteinand a target molecule that normally interacts with the protein. Thetarget can be a ligand, a substrate or a binding partner that theprotein normally interacts with (for example, epinephrine ornorepinephrine). Such assays typically include the steps of combiningthe variant protein with a candidate compound under conditions thatallow the variant protein, or fragment thereof, to interact with thetarget molecule, and to detect the formation of a complex between theprotein and the target or to detect the biochemical consequence of theinteraction with the variant protein and the target, such as any of theassociated effects of signal transduction.

Candidate compounds include, for example, 1) peptides such as solublepeptides, including Ig-tailed fusion peptides and members of randompeptide libraries (see, e.g., Lam et al., Nature 354:82-84 (1991);Houghten et al., Nature 354:84-86 (1991)) and combinatorialchemistry-derived molecular libraries made of D- and/or L-configurationamino acids; 2) phosphopeptides (e.g., members of random and partiallydegenerate, directed phosphopeptide libraries, see, e.g., Songyang etal., Cell 72:767-778 (1993)); 3) antibodies (e.g., polyclonal,monoclonal, humanized, anti-idiotypic, chimeric, and single chainantibodies as well as Fab, F(ab′)₂, Fab expression library fragments,and epitope-binding fragments of antibodies); and 4) small organic andinorganic molecules (e.g., molecules obtained from combinatorial andnatural product libraries).

One candidate compound is a soluble fragment of the variant protein thatcompetes for ligand binding. Other candidate compounds include mutantproteins or appropriate fragments containing mutations that affectvariant protein function and thus compete for ligand. Accordingly, afragment that competes for ligand, for example with a higher affinity,or a fragment that binds ligand but does not allow release, isencompassed by the invention.

The invention further includes other end point assays to identifycompounds that modulate (stimulate or inhibit) variant protein activity.The assays typically involve an assay of events in the signaltransduction pathway that indicate protein activity. Thus, theexpression of genes that are up or down-regulated in response to thevariant protein dependent signal cascade can be assayed. In oneembodiment, the regulatory region of such genes can be operably linkedto a marker that is easily detectable, such as luciferase.Alternatively, phosphorylation of the variant protein, or a variantprotein target, could also be measured. Any of the biological orbiochemical functions mediated by the variant protein can be used as anendpoint assay. These include all of the biochemical or biologicalevents described herein, in the references cited herein, incorporated byreference for these endpoint assay targets, and other functions known tothose of ordinary skill in the art.

Binding and/or activating compounds can also be screened by usingchimeric variant proteins in which an amino terminal extracellulardomain or parts thereof, an entire transmembrane domain or subregions,and/or the carboxyl terminal intracellular domain or parts thereof, canbe replaced by heterologous domains or subregions. For example, asubstrate-binding region can be used that interacts with a differentsubstrate than that which is normally recognized by a variant protein.Accordingly, a different set of signal transduction components isavailable as an end-point assay for activation. This allows for assaysto be performed in other than the specific host cell from which thevariant protein is derived.

The variant proteins are also useful in competition binding assays inmethods designed to discover compounds that interact with the variantprotein. Thus, a compound can be exposed to a variant protein underconditions that allow the compound to bind or to otherwise interact withthe variant protein. A binding partner, such as ligand, that normallyinteracts with the variant protein is also added to the mixture. If thetest compound interacts with the variant protein or its binding partner,it decreases the amount of complex formed or activity from the variantprotein. This type of assay is particularly useful in screening forcompounds that interact with specific regions of the variant protein.Hodgson, Bio/technology, 10(9), 973-80 (September 1992).

To perform cell-free drug screening assays, it is sometimes desirable toimmobilize either the variant protein or a fragment thereof, or itstarget molecule, to facilitate separation of complexes from uncomplexedforms of one or both of the proteins, as well as to accommodateautomation of the assay. Any method for immobilizing proteins onmatrices can be used in drug screening assays. In one embodiment, afusion protein containing an added domain allows the protein to be boundto a matrix. For example, glutathione-S-transferase/¹²⁵I fusion proteinscan be adsorbed onto glutathione sepharose beads (Sigma Chemical, St.Louis, Mo.) or glutathione derivatized microtitre plates, which are thencombined with the cell lysates (e.g., ³⁵S-labeled) and a candidatecompound, such as a drug candidate, and the mixture incubated underconditions conducive to complex formation (e.g., at physiologicalconditions for salt and pH). Following incubation, the beads can bewashed to remove any unbound label, and the matrix immobilized andradiolabel determined directly, or in the supernatant after thecomplexes are dissociated. Alternatively, the complexes can bedissociated from the matrix, separated by SDS-PAGE, and the level ofbound material found in the bead fraction quantitated from the gel usingstandard electrophoretic techniques.

Either the variant protein or its target molecule can be immobilizedutilizing conjugation of biotin and streptavidin. Alternatively,antibodies reactive with the variant protein but which do not interferewith binding of the variant protein to its target molecule can bederivatized to the wells of the plate, and the variant protein trappedin the wells by antibody conjugation. Preparations of the targetmolecule and a candidate compound are incubated in the variantprotein-presenting wells and the amount of complex trapped in the wellcan be quantitated. Methods for detecting such complexes, in addition tothose described above for the GST-immobilized complexes, includeimmunodetection of complexes using antibodies reactive with the proteintarget molecule, or which are reactive with variant protein and competewith the target molecule, and enzyme-linked assays that rely ondetecting an enzymatic activity associated with the target molecule.

Modulators of variant protein activity identified according to thesedrug screening assays can be used to treat a subject with a disordermediated by the protein pathway, such as CHD or aneurysm/dissection.These methods of treatment typically include the steps of administeringthe modulators of protein activity in a pharmaceutical composition to asubject in need of such treatment.

The variant proteins, or fragments thereof, disclosed herein canthemselves be directly used to treat a disorder characterized by anabsence of, inappropriate, or unwanted expression or activity of thevariant protein. Accordingly, methods for treatment include the use of avariant protein disclosed herein or fragments thereof.

In yet another aspect of the invention, variant proteins can be used as“bait proteins” in a two-hybrid assay or three-hybrid assay to identifyother proteins that bind to or interact with the variant protein and areinvolved in variant protein activity. See, e.g., U.S. Pat. No.5,283,317; Zervos et al., Cell 72:223-232 (1993); Madura et al., J BiolChem 268:12046-12054 (1993); Bartel et al., Biotechniques 14:920-924(1993); Iwabuchi et al., Oncogene 8:1693-1696 (1993); and Brent, WO94/10300. Such variant protein-binding proteins are also likely to beinvolved in the propagation of signals by the variant proteins orvariant protein targets as, for example, elements of a protein-mediatedsignaling pathway. Alternatively, such variant protein-binding proteinsare inhibitors of the variant protein.

The two-hybrid system is based on the modular nature of mosttranscription factors, which typically consist of separable DNA-bindingand activation domains. Briefly, the assay typically utilizes twodifferent DNA constructs. In one construct, the gene that codes for avariant protein is fused to a gene encoding the DNA binding domain of aknown transcription factor (e.g., GAL-4). In the other construct, a DNAsequence, from a library of DNA sequences, that encodes an unidentifiedprotein (“prey” or “sample”) is fused to a gene that codes for theactivation domain of the known transcription factor. If the “bait” andthe “prey” proteins are able to interact, in vivo, forming a variantprotein-dependent complex, the DNA-binding and activation domains of thetranscription factor are brought into close proximity. This proximityallows transcription of a reporter gene (e.g., LacZ) that is operablylinked to a transcriptional regulatory site responsive to thetranscription factor. Expression of the reporter gene can be detected,and cell colonies containing the functional transcription factor can beisolated and used to obtain the cloned gene that encodes the proteinthat interacts with the variant protein.

Antibodies Directed to Variant Proteins

The present invention also provides antibodies that selectively bind tothe variant proteins disclosed herein and fragments thereof. Suchantibodies may be used to quantitatively or qualitatively detect thevariant proteins of the present invention. As used herein, an antibodyselectively binds a target variant protein when it binds the variantprotein and does not significantly bind to non-variant proteins, i.e.,the antibody does not significantly bind to normal, wild-type, orart-known proteins that do not contain a variant amino acid sequence dueto one or more SNPs of the present invention (variant amino acidsequences may be due to, for example, nonsynonymous cSNPs, nonsense SNPsthat create a stop codon, thereby causing a truncation of a polypeptideor SNPs that cause read-through mutations resulting in an extension of apolypeptide).

As used herein, an antibody is defined in terms consistent with thatrecognized in the art: they are multi-subunit proteins produced by anorganism in response to an antigen challenge. The antibodies of thepresent invention include both monoclonal antibodies and polyclonalantibodies, as well as antigen-reactive proteolytic fragments of suchantibodies, such as Fab, F(ab)′₂, and Fv fragments. In addition, anantibody of the present invention further includes any of a variety ofengineered antigen-binding molecules such as a chimeric antibody (U.S.Pat. Nos. 4,816,567 and 4,816,397; Morrison et al., Proc Natl Acad SciUSA 81:6851 (1984); Neuberger et al., Nature 312:604 (1984)), ahumanized antibody (U.S. Pat. Nos. 5,693,762; 5,585,089 and 5,565,332),a single-chain Fv (U.S. Pat. No. 4,946,778; Ward et al., Nature 334:544(1989)), a bispecific antibody with two binding specificities (Segal etal., J Immunol Methods 248:1 (2001); Carter, J Immunol Methods 248:7(2001)), a diabody, a triabody, and a tetrabody (Todorovska et al., JImmunol Methods 248:47 (2001)), as well as a Fab conjugate (dimer ortrimer), and a minibody.

Many methods are known in the art for generating and/or identifyingantibodies to a given target antigen. Harlow, Antibodies, Cold SpringHarbor Press, N.Y. (1989). In general, an isolated peptide (e.g., avariant protein of the present invention) is used as an immunogen and isadministered to a mammalian organism, such as a rat, rabbit, hamster ormouse. Either a full-length protein, an antigenic peptide fragment(e.g., a peptide fragment containing a region that varies between avariant protein and a corresponding wild-type protein), or a fusionprotein can be used. A protein used as an immunogen may benaturally-occurring, synthetic or recombinantly produced, and may beadministered in combination with an adjuvant, including but not limitedto, Freund's (complete and incomplete), mineral gels such as aluminumhydroxide, surface active substance such as lysolecithin, pluronicpolyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin,dinitrophenol, and the like.

Monoclonal antibodies can be produced by hybridoma technology, whichimmortalizes cells secreting a specific monoclonal antibody. Kohler andMilstein, Nature 256:495 (1975). The immortalized cell lines can becreated in vitro by fusing two different cell types, typicallylymphocytes, and tumor cells. The hybridoma cells may be cultivated invitro or in vivo. Additionally, fully human antibodies can be generatedby transgenic animals. He et al., J Immunol 169:595 (2002). Fd phage andFd phagemid technologies may be used to generate and select recombinantantibodies in vitro. Hoogenboom and Chames, Immunol Today 21:371 (2000);Liu et al., J Mol Biol 315:1063 (2002). The complementarity-determiningregions of an antibody can be identified, and synthetic peptidescorresponding to such regions may be used to mediate antigen binding.U.S. Pat. No. 5,637,677.

Antibodies are preferably prepared against regions or discrete fragmentsof a variant protein containing a variant amino acid sequence ascompared to the corresponding wild-type protein (e.g., a region of avariant protein that includes an amino acid encoded by a nonsynonymouscSNP, a region affected by truncation caused by a nonsense SNP thatcreates a stop codon, or a region resulting from the destruction of astop codon due to read-through mutation caused by a SNP). Furthermore,preferred regions will include those involved in function/activityand/or protein/binding partner interaction. Such fragments can beselected on a physical property, such as fragments corresponding toregions that are located on the surface of the protein, e.g.,hydrophilic regions, or can be selected based on sequence uniqueness, orbased on the position of the variant amino acid residue(s) encoded bythe SNPs provided by the present invention. An antigenic fragment willtypically comprise at least about 8-10 contiguous amino acid residues inwhich at least one of the amino acid residues is an amino acid affectedby a SNP disclosed herein. The antigenic peptide can comprise, however,at least 12, 14, 16, 20, 25, 50, 100 (or any other number in-between) ormore amino acid residues, provided that at least one amino acid isaffected by a SNP disclosed herein.

Detection of an antibody of the present invention can be facilitated bycoupling (i.e., physically linking) the antibody or an antigen-reactivefragment thereof to a detectable substance. Detectable substancesinclude, but are not limited to, various enzymes, prosthetic groups,fluorescent materials, luminescent materials, bioluminescent materials,and radioactive materials. Examples of suitable enzymes includehorseradish peroxidase, alkaline phosphatase, β-galactosidase, oracetylcholinesterase; examples of suitable prosthetic group complexesinclude streptavidin/biotin and avidin/biotin; examples of suitablefluorescent materials include umbelliferone, fluorescein, fluoresceinisothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansylchloride or phycoerythrin; an example of a luminescent material includesluminol; examples of bioluminescent materials include luciferase,luciferin, and aequorin, and examples of suitable radioactive materialinclude ¹²⁵I, ¹³¹I, ³⁵S or ³H.

Antibodies, particularly the use of antibodies as therapeutic agents,are reviewed in: Morgan, “Antibody therapy for Alzheimer's disease,”Expert Rev Vaccines (1):53-9 (February 2003); Ross et al., “Anticancerantibodies,” Am J Clin Pathol 119(4):472-85 (April 2003); Goldenberg,“Advancing role of radiolabeled antibodies in the therapy of cancer,”Cancer Immunol Immunother 52(5):281-96 (May 2003); Epub Mar. 11, 2003;Ross et al., “Antibody-based therapeutics in oncology,” Expert RevAnticancer Ther 3(1):107-21 (February 2003); Cao et al., “Bispecificantibody conjugates in therapeutics,” Adv Drug Deliv Rev 55(2):171-97(February 2003); von Mehren et al., “Monoclonal antibody therapy forcancer,” Annu Rev Med 54:343-69 (2003); Epub Dec. 3, 2001; Hudson etal., “Engineered antibodies,” Nat Med 9(1):129-34 (January 2003); Brekkeet al., “Therapeutic antibodies for human diseases at the dawn of thetwenty-first century,” Nat Rev Drug Discov 2(1):52-62 (January 2003);Erratum in: Nat Rev Drug Discov 2(3):240 (March 2003); Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems,” Curr Opin Biotechnol 13(6):625-9 (December 2002); Andreakos etal., “Monoclonal antibodies in immune and inflammatory diseases,” CurrOpin Biotechnol 13(6):615-20 (December 2002); Kellermann et al.,“Antibody discovery: the use of transgenic mice to generate humanmonoclonal antibodies for therapeutics,” Curr Opin Biotechnol13(6):593-7 (December 2002); Pini et al., “Phage display and colonyfilter screening for high-throughput selection of antibody libraries,”Comb Chem High Throughput Screen 5(7):503-10 (November 2002); Batra etal., “Pharmacokinetics and biodistribution of genetically engineeredantibodies,” Curr Opin Biotechnol 13(6):603-8 (December 2002); andTangri et al., “Rationally engineered proteins or antibodies with absentor reduced immunogenicity,” Curr Med Chem 9(24):2191-9 (December 2002).

Uses of Antibodies

Antibodies can be used to isolate the variant proteins of the presentinvention from a natural cell source or from recombinant host cells bystandard techniques, such as affinity chromatography orimmunoprecipitation. In addition, antibodies are useful for detectingthe presence of a variant protein of the present invention in cells ortissues to determine the pattern of expression of the variant proteinamong various tissues in an organism and over the course of normaldevelopment or disease progression. Further, antibodies can be used todetect variant protein in situ, in vitro, in a bodily fluid, or in acell lysate or supernatant in order to evaluate the amount and patternof expression. Also, antibodies can be used to assess abnormal tissuedistribution, abnormal expression during development, or expression inan abnormal condition, such as in CHD or aneurysm/dissection, or duringstatin treatment. Additionally, antibody detection of circulatingfragments of the full-length variant protein can be used to identifyturnover.

Antibodies to the variant proteins of the present invention are alsouseful in pharmacogenomic analysis. Thus, antibodies against variantproteins encoded by alternative SNP alleles can be used to identifyindividuals that require modified treatment modalities.

Further, antibodies can be used to assess expression of the variantprotein in disease states such as in active stages of the disease or inan individual with a predisposition to a disease related to theprotein's function, such as CHD or aneurysm/dissection, or during thecourse of a treatment regime, such as during statin treatment.Antibodies specific for a variant protein encoded by a SNP-containingnucleic acid molecule of the present invention can be used to assay forthe presence of the variant protein, such as to diagnose CHD oraneurysm/dissection or to predict an individual's response to statintreatment or predisposition/susceptibility to CHD oraneurysm/dissection, as indicated by the presence of the variantprotein.

Antibodies are also useful as diagnostic tools for evaluating thevariant proteins in conjunction with analysis by electrophoreticmobility, isoelectric point, tryptic peptide digest, and other physicalassays well known in the art.

Antibodies are also useful for tissue typing. Thus, where a specificvariant protein has been correlated with expression in a specifictissue, antibodies that are specific for this protein can be used toidentify a tissue type.

Antibodies can also be used to assess aberrant subcellular localizationof a variant protein in cells in various tissues. The diagnostic usescan be applied, not only in genetic testing, but also in monitoring atreatment modality. Accordingly, where treatment is ultimately aimed atcorrecting the expression level or the presence of variant protein oraberrant tissue distribution or developmental expression of a variantprotein, antibodies directed against the variant protein or relevantfragments can be used to monitor therapeutic efficacy.

The antibodies are also useful for inhibiting variant protein function,for example, by blocking the binding of a variant protein to a bindingpartner. These uses can also be applied in a therapeutic context inwhich treatment involves inhibiting a variant protein's function. Anantibody can be used, for example, to block or competitively inhibitbinding, thus modulating (agonizing or antagonizing) the activity of avariant protein. Antibodies can be prepared against specific variantprotein fragments containing sites required for function or against anintact variant protein that is associated with a cell or cell membrane.For in vivo administration, an antibody may be linked with an additionaltherapeutic payload such as a radionuclide, an enzyme, an immunogenicepitope, or a cytotoxic agent. Suitable cytotoxic agents include, butare not limited to, bacterial toxin such as diphtheria, and plant toxinsuch as ricin. The in vivo half-life of an antibody or a fragmentthereof may be lengthened by pegylation through conjugation topolyethylene glycol. Leong et al., Cytokine 16:106 (2001).

The invention also encompasses kits for using antibodies, such as kitsfor detecting the presence of a variant protein in a test sample. Anexemplary kit can comprise antibodies such as a labeled or labelableantibody and a compound or agent for detecting variant proteins in abiological sample; means for determining the amount, or presence/absenceof variant protein in the sample; means for comparing the amount ofvariant protein in the sample with a standard; and instructions for use.

Vectors and Host Cells

The present invention also provides vectors containing theSNP-containing nucleic acid molecules described herein. The term“vector” refers to a vehicle, preferably a nucleic acid molecule, whichcan transport a SNP-containing nucleic acid molecule. When the vector isa nucleic acid molecule, the SNP-containing nucleic acid molecule can becovalently linked to the vector nucleic acid. Such vectors include, butare not limited to, a plasmid, single or double stranded phage, a singleor double stranded RNA or DNA viral vector, or artificial chromosome,such as a BAC, PAC, YAC, or MAC.

A vector can be maintained in a host cell as an extrachromosomal elementwhere it replicates and produces additional copies of the SNP-containingnucleic acid molecules. Alternatively, the vector may integrate into thehost cell genome and produce additional copies of the SNP-containingnucleic acid molecules when the host cell replicates.

The invention provides vectors for the maintenance (cloning vectors) orvectors for expression (expression vectors) of the SNP-containingnucleic acid molecules. The vectors can function in prokaryotic oreukaryotic cells or in both (shuttle vectors).

Expression vectors typically contain cis-acting regulatory regions thatare operably linked in the vector to the SNP-containing nucleic acidmolecules such that transcription of the SNP-containing nucleic acidmolecules is allowed in a host cell. The SNP-containing nucleic acidmolecules can also be introduced into the host cell with a separatenucleic acid molecule capable of affecting transcription. Thus, thesecond nucleic acid molecule may provide a trans-acting factorinteracting with the cis-regulatory control region to allowtranscription of the SNP-containing nucleic acid molecules from thevector. Alternatively, a trans-acting factor may be supplied by the hostcell. Finally, a trans-acting factor can be produced from the vectoritself. It is understood, however, that in some embodiments,transcription and/or translation of the nucleic acid molecules can occurin a cell-free system.

The regulatory sequences to which the SNP-containing nucleic acidmolecules described herein can be operably linked include promoters fordirecting mRNA transcription. These include, but are not limited to, theleft promoter from bacteriophage λ, the lac, TRP, and TAC promoters fromE. coli, the early and late promoters from SV40, the CMV immediate earlypromoter, the adenovirus early and late promoters, and retroviruslong-terminal repeats.

In addition to control regions that promote transcription, expressionvectors may also include regions that modulate transcription, such asrepressor binding sites and enhancers. Examples include the SV40enhancer, the cytomegalovirus immediate early enhancer, polyomaenhancer, adenovirus enhancers, and retrovirus LTR enhancers.

In addition to containing sites for transcription initiation andcontrol, expression vectors can also contain sequences necessary fortranscription termination and, in the transcribed region, aribosome-binding site for translation. Other regulatory control elementsfor expression include initiation and termination codons as well aspolyadenylation signals. A person of ordinary skill in the art would beaware of the numerous regulatory sequences that are useful in expressionvectors. See, e.g., Sambrook and Russell, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Laboratory Press, N.Y. (2000).

A variety of expression vectors can be used to express a SNP-containingnucleic acid molecule. Such vectors include chromosomal, episomal, andvirus-derived vectors, for example, vectors derived from bacterialplasmids, from bacteriophage, from yeast episomes, from yeastchromosomal elements, including yeast artificial chromosomes, fromviruses such as baculoviruses, papovaviruses such as SV40, Vacciniaviruses, adenoviruses, poxviruses, pseudorabies viruses, andretroviruses. Vectors can also be derived from combinations of thesesources such as those derived from plasmid and bacteriophage geneticelements, e.g., cosmids and phagemids. Appropriate cloning andexpression vectors for prokaryotic and eukaryotic hosts are described inSambrook and Russell, Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory Press, N.Y. (2000).

The regulatory sequence in a vector may provide constitutive expressionin one or more host cells (e.g., tissue specific expression) or mayprovide for inducible expression in one or more cell types such as bytemperature, nutrient additive, or exogenous factor, e.g., a hormone orother ligand. A variety of vectors that provide constitutive orinducible expression of a nucleic acid sequence in prokaryotic andeukaryotic host cells are well known to those of ordinary skill in theart.

A SNP-containing nucleic acid molecule can be inserted into the vectorby methodology well-known in the art. Generally, the SNP-containingnucleic acid molecule that will ultimately be expressed is joined to anexpression vector by cleaving the SNP-containing nucleic acid moleculeand the expression vector with one or more restriction enzymes and thenligating the fragments together. Procedures for restriction enzymedigestion and ligation are well known to those of ordinary skill in theart.

The vector containing the appropriate nucleic acid molecule can beintroduced into an appropriate host cell for propagation or expressionusing well-known techniques. Bacterial host cells include, but are notlimited to, Escherichia coli, Streptomyces spp., and Salmonellatyphimurium. Eukaryotic host cells include, but are not limited to,yeast, insect cells such as Drosophila spp., animal cells such as COSand CHO cells, and plant cells.

As described herein, it may be desirable to express the variant peptideas a fusion protein. Accordingly, the invention provides fusion vectorsthat allow for the production of the variant peptides. Fusion vectorscan, for example, increase the expression of a recombinant protein,increase the solubility of the recombinant protein, and aid in thepurification of the protein by acting, for example, as a ligand foraffinity purification. A proteolytic cleavage site may be introduced atthe junction of the fusion moiety so that the desired variant peptidecan ultimately be separated from the fusion moiety. Proteolytic enzymessuitable for such use include, but are not limited to, factor Xa,thrombin, and enterokinase. Typical fusion expression vectors includepGEX (Smith et al., Gene 67:31-40 (1988)), pMAL (New England Biolabs,Beverly, Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuseglutathione S-transferase (GST), maltose E binding protein, or proteinA, respectively, to the target recombinant protein. Examples of suitableinducible non-fusion E. coli expression vectors include pTrc (Amann etal., Gene 69:301-315 (1988)) and pET 11 d (Studier et al., GeneExpression Technology: Methods in Enzymology 185:60-89 (1990)).

Recombinant protein expression can be maximized in a bacterial host byproviding a genetic background wherein the host cell has an impairedcapacity to proteolytically cleave the recombinant protein (S.Gottesman, Gene Expression Technology: Methods in Enzymology185:119-128, Academic Press, Calif. (1990)). Alternatively, the sequenceof the SNP-containing nucleic acid molecule of interest can be alteredto provide preferential codon usage for a specific host cell, forexample, E. coli. Wada et al., Nucleic Acids Res 20:2111-2118 (1992).

The SNP-containing nucleic acid molecules can also be expressed byexpression vectors that are operative in yeast. Examples of vectors forexpression in yeast (e.g., S. cerevisiae) include pYepSec1 (Baldari etal., EMBO J 6:229-234 (1987)), pMFa (Kurjan et al., Cell 30:933-943(1982)), pJRY88 (Schultz et al., Gene 54:113-123 (1987)), and pYES2(Invitrogen Corporation, San Diego, Calif.).

The SNP-containing nucleic acid molecules can also be expressed ininsect cells using, for example, baculovirus expression vectors.Baculovirus vectors available for expression of proteins in culturedinsect cells (e.g., Sf 9 cells) include the pAc series (Smith et al.,Mol Cell Biol 3:2156-2165 (1983)) and the pVL series (Lucklow et al.,Virology 170:31-39 (1989)).

In certain embodiments of the invention, the SNP-containing nucleic acidmolecules described herein are expressed in mammalian cells usingmammalian expression vectors. Examples of mammalian expression vectorsinclude pCDM8 (B. Seed, Nature 329:840(1987)) and pMT2PC (Kaufman etal., EMBO J 6:187-195 (1987)).

The invention also encompasses vectors in which the SNP-containingnucleic acid molecules described herein are cloned into the vector inreverse orientation, but operably linked to a regulatory sequence thatpermits transcription of antisense RNA. Thus, an antisense transcriptcan be produced to the SNP-containing nucleic acid sequences describedherein, including both coding and non-coding regions. Expression of thisantisense RNA is subject to each of the parameters described above inrelation to expression of the sense RNA (regulatory sequences,constitutive or inducible expression, tissue-specific expression).

The invention also relates to recombinant host cells containing thevectors described herein. Host cells therefore include, for example,prokaryotic cells, lower eukaryotic cells such as yeast, othereukaryotic cells such as insect cells, and higher eukaryotic cells suchas mammalian cells.

The recombinant host cells can be prepared by introducing the vectorconstructs described herein into the cells by techniques readilyavailable to persons of ordinary skill in the art. These include, butare not limited to, calcium phosphate transfection,DEAE-dextran-mediated transfection, cationic lipid-mediatedtransfection, electroporation, transduction, infection, lipofection, andother techniques such as those described in Sambrook and Russell,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory,Cold Spring Harbor Laboratory Press, N.Y. (2000).

Host cells can contain more than one vector. Thus, differentSNP-containing nucleotide sequences can be introduced in differentvectors into the same cell. Similarly, the SNP-containing nucleic acidmolecules can be introduced either alone or with other nucleic acidmolecules that are not related to the SNP-containing nucleic acidmolecules, such as those providing trans-acting factors for expressionvectors. When more than one vector is introduced into a cell, thevectors can be introduced independently, co-introduced, or joined to thenucleic acid molecule vector.

In the case of bacteriophage and viral vectors, these can be introducedinto cells as packaged or encapsulated virus by standard procedures forinfection and transduction. Viral vectors can be replication-competentor replication-defective. In the case in which viral replication isdefective, replication can occur in host cells that provide functionsthat complement the defects.

Vectors generally include selectable markers that enable the selectionof the subpopulation of cells that contain the recombinant vectorconstructs. The marker can be inserted in the same vector that containsthe SNP-containing nucleic acid molecules described herein or may be ina separate vector. Markers include, for example, tetracycline orampicillin-resistance genes for prokaryotic host cells, anddihydrofolate reductase or neomycin resistance genes for eukaryotic hostcells. However, any marker that provides selection for a phenotypictrait can be effective.

While the mature variant proteins can be produced in bacteria, yeast,mammalian cells, and other cells under the control of the appropriateregulatory sequences, cell-free transcription and translation systemscan also be used to produce these variant proteins using RNA derivedfrom the DNA constructs described herein.

Where secretion of the variant protein is desired, which is difficult toachieve with multi-transmembrane domain containing proteins such asG-protein-coupled receptors (GPCRs), appropriate secretion signals canbe incorporated into the vector. The signal sequence can be endogenousto the peptides or heterologous to these peptides.

Where the variant protein is not secreted into the medium, the proteincan be isolated from the host cell by standard disruption procedures,including freeze/thaw, sonication, mechanical disruption, use of lysingagents, and the like. The variant protein can then be recovered andpurified by well-known purification methods including, for example,ammonium sulfate precipitation, acid extraction, anion or cationicexchange chromatography, phosphocellulose chromatography,hydrophobic-interaction chromatography, affinity chromatography,hydroxylapatite chromatography, lectin chromatography, or highperformance liquid chromatography.

It is also understood that, depending upon the host cell in whichrecombinant production of the variant proteins described herein occurs,they can have various glycosylation patterns, or may benon-glycosylated, as when produced in bacteria. In addition, the variantproteins may include an initial modified methionine in some cases as aresult of a host-mediated process.

For further information regarding vectors and host cells, see CurrentProtocols in Molecular Biology, John Wiley & Sons, N.Y.

Uses of Vectors and Host Cells, and Transgenic Animals

Recombinant host cells that express the variant proteins describedherein have a variety of uses. For example, the cells are useful forproducing a variant protein that can be further purified into apreparation of desired amounts of the variant protein or fragmentsthereof. Thus, host cells containing expression vectors are useful forvariant protein production.

Host cells are also useful for conducting cell-based assays involvingthe variant protein or variant protein fragments, such as thosedescribed above as well as other formats known in the art. Thus, arecombinant host cell expressing a variant protein is useful forassaying compounds that stimulate or inhibit variant protein function.Such an ability of a compound to modulate variant protein function maynot be apparent from assays of the compound on the native/wild-typeprotein, or from cell-free assays of the compound. Recombinant hostcells are also useful for assaying functional alterations in the variantproteins as compared with a known function.

Genetically-engineered host cells can be further used to producenon-human transgenic animals. A transgenic animal is preferably anon-human mammal, for example, a rodent, such as a rat or mouse, inwhich one or more of the cells of the animal include a transgene. Atransgene is exogenous DNA containing a SNP of the present inventionwhich is integrated into the genome of a cell from which a transgenicanimal develops and which remains in the genome of the mature animal inone or more of its cell types or tissues. Such animals are useful forstudying the function of a variant protein in vivo, and identifying andevaluating modulators of variant protein activity. Other examples oftransgenic animals include, but are not limited to, non-human primates,sheep, dogs, cows, goats, chickens, and amphibians. Transgenic non-humanmammals such as cows and goats can be used to produce variant proteinswhich can be secreted in the animal's milk and then recovered.

A transgenic animal can be produced by introducing a SNP-containingnucleic acid molecule into the male pronuclei of a fertilized oocyte,e.g., by microinjection or retroviral infection, and allowing the oocyteto develop in a pseudopregnant female foster animal. Any nucleic acidmolecules that contain one or more SNPs of the present invention canpotentially be introduced as a transgene into the genome of a non-humananimal.

Any of the regulatory or other sequences useful in expression vectorscan form part of the transgenic sequence. This includes intronicsequences and polyadenylation signals, if not already included. Atissue-specific regulatory sequence(s) can be operably linked to thetransgene to direct expression of the variant protein in particularcells or tissues.

Methods for generating transgenic animals via embryo manipulation andmicroinjection, particularly animals such as mice, have becomeconventional in the art and are described, for example, in U.S. Pat.Nos. 4,736,866 and 4,870,009, both by Leder et al.; U.S. Pat. No.4,873,191 by Wagner et al., and in B. Hogan, Manipulating the MouseEmbryo, Cold Spring Harbor Laboratory Press, N.Y. (1986). Similarmethods are used for production of other transgenic animals. Atransgenic founder animal can be identified based upon the presence ofthe transgene in its genome and/or expression of transgenic mRNA intissues or cells of the animals. A transgenic founder animal can then beused to breed additional animals carrying the transgene. Moreover,transgenic animals carrying a transgene can further be bred to othertransgenic animals carrying other transgenes. A transgenic animal alsoincludes a non-human animal in which the entire animal or tissues in theanimal have been produced using the homologously recombinant host cellsdescribed herein.

In another embodiment, transgenic non-human animals can be producedwhich contain selected systems that allow for regulated expression ofthe transgene. One example of such a system is the cre/loxP recombinasesystem of bacteriophage P1. Lakso et al., PNAS 89:6232-6236 (1992).Another example of a recombinase system is the FLP recombinase system ofS. cerevisiae. O'Gorman et al., Science 251:1351-1355 (1991). If acre/loxP recombinase system is used to regulate expression of thetransgene, animals containing transgenes encoding both the Crerecombinase and a selected protein are generally needed. Such animalscan be provided through the construction of “double” transgenic animals,e.g., by mating two transgenic animals, one containing a transgeneencoding a selected variant protein and the other containing a transgeneencoding a recombinase.

Clones of the non-human transgenic animals described herein can also beproduced according to the methods described, for example, in I. Wilmutet al., Nature 385:810-813 (1997) and PCT International Publication Nos.WO 97/07668 and WO 97/07669. In brief, a cell (e.g., a somatic cell)from the transgenic animal can be isolated and induced to exit thegrowth cycle and enter G_(o) phase. The quiescent cell can then befused, e.g., through the use of electrical pulses, to an enucleatedoocyte from an animal of the same species from which the quiescent cellis isolated. The reconstructed oocyte is then cultured such that itdevelops to morula or blastocyst and then transferred to pseudopregnantfemale foster animal. The offspring born of this female foster animalwill be a clone of the animal from which the cell (e.g., a somatic cell)is isolated.

Transgenic animals containing recombinant cells that express the variantproteins described herein are useful for conducting the assays describedherein in an in vivo context. Accordingly, the various physiologicalfactors that are present in vivo and that could influence ligand orsubstrate binding, variant protein activation, signal transduction, orother processes or interactions, may not be evident from in vitrocell-free or cell-based assays. Thus, non-human transgenic animals ofthe present invention may be used to assay in vivo variant proteinfunction as well as the activities of a therapeutic agent or compoundthat modulates variant protein function/activity or expression. Suchanimals are also suitable for assessing the effects of null mutations(i.e., mutations that substantially or completely eliminate one or morevariant protein functions).

For further information regarding transgenic animals, see Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems,” Curr Opin Biotechnol 13(6):625-9 (December 2002); Petters etal., “Transgenic animals as models for human disease,” Transgenic Res9(4-5):347-51, discussion 345-6 (2000); Wolf et al., “Use of transgenicanimals in understanding molecular mechanisms of toxicity,” J PharmPharmacol 50(6):567-74 (June 1998); Echelard, “Recombinant proteinproduction in transgenic animals,” Curr Opin Biotechnol 7(5):536-40(October 1996); Houdebine, “Transgenic animal bioreactors,” TransgenicRes 9(4-5):305-20 (2000); Pirity et al., “Embryonic stem cells, creatingtransgenic animals,” Methods Cell Biol 57:279-93 (1998); and Robl etal., “Artificial chromosome vectors and expression of complex proteinsin transgenic animals,” Theriogenology 59(1):107-13 (January 2003).

EXAMPLES

The following examples are offered to illustrate, but not limit, theclaimed invention.

Example 1: Genetic Polymorphism Designated hCV3054799 in KIF6 Gene isAssociated with Risk of CHD and Benefit from Statin Therapy forReduction of Coronary Events

In order to identify genetic markers associated with CHD (particularlyMI, including recurrent MI) or the effect of statin treatment on CHD,samples were genotyped in two clinical trials: the Cholesterol andRecurrent Events (CARE) study (a randomized multicentral double-blindedtrial on secondary prevention of MI with pravastatin (Pravachol®); Sackset al., Am. J. Cardiol. 68: 1436-1446 [1991]), and the West of ScotlandCoronary Prevention Study (WOSCOPS) study (a randomized multicentraldouble-blinded trial on primary prevention of CHD with pravastatin(Pravachol®); Shepherd et al., N Eng J Med 333 (20), pp. 1301-7, Nov.16, 1995; Packard et al., N Eng J Med 343 (16), pp. 1148-55, Oct. 19,2000).

A well-documented MI was one of the enrollment criteria for entry intothe CARE study. Patients were enrolled in the CARE trial from 80participating study centers. Men and post-menopausal women were eligiblefor the trial if they had had an acute MI between 3 and 20 months priorto randomization, were 21 to 75 years of age, and had plasma totalcholesterol levels of less than 240 mg/deciliter, LDL cholesterol levelsof 115 to 174 mg/deciliter, fasting triglyceride levels of less than 350mg/deciliter, fasting glucose levels of no more than 220 mg/deciliter,left ventricular ejection fractions of no less than 25%, and nosymptomatic congestive heart failure. Patients were randomized toreceive either 40 mg of pravastatin once daily or a matching placebo.The primary endpoint of the trial was death from CHD or nonfatal MI andthe median duration of follow-up was 5.0 years (range, 4.0 to 6.2years). For this genetic study of CARE, a composite endpoint comprisedof fatal or nonfatal recurrent MI was used.

The designs of the original WOSCOPS cohort and the nested case-controlstudy have been described (Shepherd et al., N Eng J Med 333 (20), pp.1301-7, Nov. 16, 1995; Packard et al., N Eng J Med 343 (16), pp.1148-55, Oct. 19, 2000). The objective of the WOSCOPS trial was toassess pravastatin efficacy at reducing risk of primary MI or coronarydeath among Scottish men with hypercholesterolemia (fasting LDLcholesterol >155 mg/dl). Participants in the WOSCOPS study were 45-64years of age and followed for an average of 4.9 years for coronaryevents. The nested case-control study included as cases all WOSCOPSpatients who experienced a coronary event (confirmed nonfatal MI, deathfrom CHD, or a revascularization procedure; N=580). Controls were age-and smoking-matched to unaffected patients.

For genotyping SNPs in CARE patient samples, DNA was extracted fromblood samples using conventional DNA extraction methods such as theQIAamp kit from Qiagen. Genotypes were obtained by a method similar tothat described by lannone (M. A. Iannone et al., Cytometry 39(2):131-140[Feb. 1, 2000]; also described in section “SNP DETECTION REAGENTS,”supra). Briefly, target DNA was amplified by multiplex PCR, theamplified product was submitted to a multiplex oligo ligation assay(OLA), the specific ligated products were hybridized to unique universal“ZIP code” oligomer sequences covalently attached to Luminex xMAP®Multi-Analyte COOH Microspheres, and these hybridizationproducts/microspheres were detected in a rapid automated multiplexsystem (Luminex 100 instrument).

References are made to Tables 5 and 6 for data supporting the conclusionthat individuals carrying certain hCV3054799 Arg allele had an increasedrisk of developing recurrent MI in CARE and CHD events in WOSCOPS, andthat they responded to statin treatment by showing a decrease in CHDevents. In the placebo arm of CARE, carriers of the KIF6 719Arg riskallele had a hazard ratio for recurrent MI of 1.50 (95% CI 1.05 to 2.15,Table 5) in a model adjusted for age, sex, smoking, history ofhypertension, history of diabetes, body mass index, LDL-C, and HDL-C. Inthe placebo arm of WOSCOPS, it was found that carriers of the KIF6719Arg risk allele had an odds ratio for CHD of 1.55 (95% CI 1.14 to2.09, Table 5) in a model adjusted for history of hypertension, historyof diabetes, body mass index, LDL-C, and HDL-C(cases and controls werematched for age and smoking status).

In CARE, pravastatin treatment reduced the relative risk of recurrent MIby 37% among carriers of the 719Arg risk allele (adjusted HR 0.63, 95%CI 0.46 to 0.87, Table 6), and among carriers in WOSCOPS pravastatintreatment resulted in an odds ratio for primary CHD of 0.50 (95% CI 0.38to 0.68, Table 6). The genotype frequencies for KIF6 Trp719Arg were40.6%, 46.5%, and 12.8%, for TrpTrp, ArgTrp, and ArgArg, respectively,in the CARE cohort. In the WOSCOPS control group, the frequencies were44.2%, 43.6%, and 12.2%, respectively. Data in Tables 5 and 6 werederived as follows:

In analyzing the CARE patients, statistical analysis was performed withSAS version 9. Cox proportional hazard models (Wald tests) were used inCARE to assess the association of genotype with both the risk ofincident MI in the placebo arm and the effect of pravastatin on MIcompared to placebo in subgroups defined by genotypes. In analyzing theWOSCOPS patients, a conditional logistic regression model was used inWOSCOPS given that the controls had been previously matched to thecases. The column entitled “On-trial MI” lists the number of patientswho suffered a recurrent MI during the clinical trial period.

HR stands for Hazard Ratio, which is a concept similar to Odds Ratio(OR). The HR in event-free survival analysis is the effect of anexplanatory variable on the hazard or risk of an event. For examples, itdescribes the likelihood of developing MI based on comparison of rate ofcoronary events between carriers of the certain allele and noncarriers;therefore, HR=1.5 would mean that carriers of the certain allele have50% higher risk of coronary events during the study follow up thannon-carriers. HR can also describe the effect of statin therapy oncoronary events based on comparison of rate of coronary events betweenpatient treated with statin and patient treated with placebo (or otherstatin) in subgroups defined by SNP genotype; therefore, HR=0.5 wouldmean that, for example, carriers of the certain allele, had 50%reduction of coronary events by statin therapy as compared to placebo.In Table 6, p interaction values were calculated. An interaction (oreffect modification) is formed when a third variable modifies therelation between an exposure and outcome. A p interaction <0.05indicates that a third variable (genotype) modifies the relation betweenan exposure (statin treatment) and outcome (MI). Genotype and druginteraction is present when the effect of statins (incidence rate ofdisease in statin-tretaed group, as compared to placebo) differs inpartients with different genotypes. The hCV3054799 risk allele predictedrisk of MI in CARE and was associated with odds of CHD in WOSCOPS.

In both trials, carriers of the KIF6 719Arg risk allele (about 60% ofpopulation) received significant benefit from pravastatin therapy interms of reduction of coronary events whereas non-carriers did notreceive significant benefit. Moreover, the nominal risk reduction wasgreater in carriers of the KIF6 719Arg allele than in non-carriers: inCARE, a significant risk reduction of 37% was observed in carrierswhereas an insignificant risk reduction of 20% was observed innoncarriers, and in WOSCOPS, a significant risk reduction of 50% wasobserved in carriers whereas an insignificant risk reduction of 9% wasobserved in noncarriers. A significant interaction between genotype andtreatment was observed in WOSCOPS (p=0.01 interaction) and did not reachsignificance in CARE (p=0.39) (Table 6) (Iakoubova et al., “Associationof the Trp7l9Arg polymorphism in kinesin-like protein 6 with myocardialinfarction and coronary heart disease in 2 prospective trials: the CAREand WOSCOPS trials”, J Am Coll Cardiol. 2008 January 29; 51(4):435-43,which is incorporated herein by reference in its entirety).

Example 2: Carriers of the Risk Allele of hCV3054799 Benefited fromAtorvastatin (Lipitor®) Treatment in Addition to Pravastatin(Pravachol®) Treatment

As discussed earlier in Example 1, carriers of the KIF6 719Arg riskallele had a greater reduction of recurrent MI and primary CHD in theCARE and WOSCOPS trials (respectively) by pravastatin (Pravachol®)treatment, as compared to placebo, than did non-carriers (in the placeboarms of these studies, it was observed that carriers of the KIF6 719Argallele had a 50% greater incidence of CHD compared to non-carriers).Given the previous observation that in CARE and WOSCOPS, carriers of theKIF6 719Arg risk variant had a greater reduction of CHD events frompravastatin therapy, as compared to placebo, than non-carriers, it wasdetermined whether in the PROVE-IT (“Pravastatin or AtorvastatinEvaluation and Infection Therapy”) study, intensive therapy withhigh-dose atorvastatin (Lipitor®), as compared with standard-dosepravastatin treatment, would result in a greater reduction of recurrentCHD events in carriers than in non-carriers. In addition, with thistrial, it was determined whether carriers of the KIF6 719Arg risk allelewould benefit from intensive therapy with high-dose atorvastatin ascompared with standard-dose pravastatin, just as carriers of the KIF6719Arg risk allele benefited from standard-dose pravastation as comparedwith placebo.

To further study the effect of statin treatment on KIF6 719Arg carriers,a genetic association study was conducted in a population derived fromthe study referred to as “Pravastatin or Atorvastatin Evaluation andInfection Therapy—Thrombolysis in Myocardial Infraction” (PROVE-IT-TIMI)that assessed the effect of atorvastatin as compared to pravastatin inthe prevention of death or major cardiovascular events in patients withan acute coronary syndrome. The design of PROVE-IT protocol has beendescribed previously (Christopher P. Cannon., et al., Intensive versusmoderate lipid lowering with statins after acute coronary syndromes. NEngl J Med, 2004, 350 (15): pp. 1495-04).

Briefly, it was a randomized trial that used a two-by-two factorialdesign to compare the effect of intensive statin therapy (80 mg ofatorvastatin per day) and moderate statin therapy (40 mg of pravastatinper day) on the risk of recurrent coronary events after acute coronarysyndromes. Patients were followed for 18 to 36 months, with an averagefollow-up of 24 months. This genetic study comprised 2,061 patients whoprovided written informed consent for genetic analysis among 4,162patients in PROVE-IT cohort.

For this genetic analysis, the evaluation was limited to PROVE-ITpatients who (1) underwent successful DNA extraction and genotyping asoutlined herein, 32 patients were excluded due to inadequate quantity orquality of DNA; (2) are white (since non-whites comprised only 10.4% ofthe population that did not provide sufficient power for a separateanalysis, and population stratification might have compromised acombined analysis); (3) had information for all covariates adjusted inmodel 1 and 2, 93 patients were excluded because of the missinginformation. Of the 1,724 patients who met the criteria listed above,1344 (78.0%) were male. For this genetic study, a composite end point ofdeath from any cause or major cardiovascular events was used, whichincluded MI, documented unstable angina requiring hospitalization,revascularization (performed at least 30 days after randomization), andstroke (Iakoubova et al., “Polymorphism in KIF6 gene and benefit fromstatins after acute coronary syndromes: results from the PROVE IT-TIMI22 study”, J Am Coll Cardiol. 2008 Jan. 29; 51(4):449-55). This studywas approved by institutional review boards of the Brigham and Women'sHospital and all participating centers.

KIF6 genotypes were determined using allele-specific real-time PCR aspreviously described. Cox proportional hazard models (Wald tests) wereused to assess the effect of atorvastatin-treatment on incident CHD inthe KIF6 719Arg carriers and noncarriers. Continuous variables testedwere age, baseline LDL-C, and baseline HDL-C levels. Categoricalvariables tested were smoking (current versus non-current),hypertension, and baseline diabetes. All reported p values aretwo-sided.

The high-dose atorvastatin therapy, as compared to standard-dosepravastatin therapy, resulted in substantial and significant benefit incarriers of the KIF6 719Arg allele, but not in non-carriers. In carriers(58.7% of the PROVE-IT population) therapy with high-dose atorvastatin,as compared to standard-dose of pravastatin, reduced the relative riskof coronary events by 44%. The hazard ratio was 0.56 (95% confidenceinterval 0.42 to 0.75; P<0.0001) after adjustment for age, sex, smoking,history of hypertension, history of diabetes, base-line levels of LDL-Cand HDL-C. In contrast, in non-carriers, high-dose atorvastatin therapy,as compared to standard-dose pravastatin, resulted in the adjustedhazard ratio of 0.97 (95% confidence interval 0.72 to 1.31; P=0.84).This difference between carriers and non-carriers in benefit fromhigh-dose of atorvastatin was significant (P=0.01 for interactionbetween genotype and treatment) (Table 7).

Thus, data in Table 7 shows the effect of Atorvastatin, as compared toPravastatin, on incidence of coronary events in the PROVE-IT cohort. Asseen from Table 7, carriers of the KIF6 719Arg allele benefited from theatorvastatin therapy, as compared to pravastatin, and noncarriers didnot receive significant benefit from atorvastatin. This finding,together with the previous observation in the CARE and WOSCOPS studiesthat carriers of the KIF6 719Arg risk allele received greater benefitfrom pravastatin than non-carriers, as compared to placebo, indicatethat both statins (pravastatin and atorvastatin) substantially andsignificantly reduce coronary events in carriers of the KIF6 719Argallele but do not substantially and significantly reduce coronary eventsin non-carriers. Furthermore, high-dose atorvastatin is more effectivethan pravastatin in reducing coronary events in carriers of the KIF6719Arg allele (Iakoubova et al., “Polymorphism in KIF6 gene and benefitfrom statins after acute coronary syndromes: results from the PROVEIT-TIMI 22 study”, J Am Coll Cardiol. 2008 Jan. 29; 51(4):449-55, whichis incorporated herein by reference in its entirety).

Thus, because it has been shown herein in Example 2 that carriers of theKIF6 719Arg allele benefit from multiple different types of statins(e.g., both pravastatin, which is a hydrophilic statin, andatorvastatin, which is a lipophilic statin), this SNP, as well as theother statin-response associated SNPs disclosed herein, is expected tohave similar utilities across the entire class of statins, particularlysince it has specifically been shown to be useful for both hydrophilicand lipophilic statins. Therefore, the KIF6 Trp719Arg SNP is broadlyuseful in predicting the therapeutic effect for the entire class ofstatins, such as for determining whether an individual will benefit fromany of the statins, including, but not limited to, fluvastatin(Lescol®), lovastatin (Mevacor®), rosuvastatin (Crestor®), andsimvastatin (Zocor®), as well as combination therapies that include astatin such as simvastatin+ezetimibe (Vytorin®), lovastatin+niacinextended-release (Advicor®), and atorvastatin+amlodipine besylate(Caduet®).

Moreover, in carriers of the KIF6 719Arg allele, the substantial andsignificant benefit from high-dose atorvastatin therapy, compared withstandard-dose pravastatin therapy, was evident as early as 30 days afterrandomization and remained significant throughout the trial: theunadjusted hazard ratio at 30 days was 0.18 (95% CI, 0.04 to 0.81). Incontrast to the early benefit seen in carriers of the KIF6 719Argallele, in noncarriers there was no significant benefit of intensivetherapy, compared with moderate therapy, at any time point.

Since LDL-C cholesterol, CRP, and triglyceride levels are risk factorsfor cardiovascular events and can be reduced by intensive statintherapy, it was analyzed whether the changes in the levels of these riskfactors in response to treatment with either high-dose atorvastatin orwith standard-dose pravastatin differed between carriers and noncarriersof the KIF6 719Arg allele. No evidence was found in either the high-doseatorvastatin group or in the standard-dose pravastatin group that theserisk factors differed between carriers and noncarriers at any timeduring therapy. Specifically, in both treatment groups, no significantdifferences in median LDL-C, CRP, or triglyceride levels were found whencomparing carriers and noncarriers of the KIF6 719Arg allele at baselineor at any scheduled visit during the study (p≥0.3).

These data suggest that this early superiority of intensive statintherapy for reduction of coronary event in carriers may be due to anearly, plaque-stabilizing effect of the intensive treatment regimen, apleiotropic effect that has been proposed to explain the early benefitfrom statin therapy that appears not to be due to LDL-lowering. Apleiotropic mechanism would be consistent with the observation describedherein that on-treatment median LDL-C levels did not differ betweencarriers and noncarriers. Additionally, this early benefit fromintensive statin therapy in carriers of the KIF6 719Arg allele is likelyto be distinct from anti-inflammatory mechanisms related to thereduction of CRP levels since carriers and noncarriers of the KIF6719Arg allele did not differ in median CRP levels at baseline or duringthe trial (Iakoubova et al., “Polymorphism in KIF6 gene and benefit fromstatins after acute coronary syndromes: results from the PROVE IT-TIMI22 study”, J Am Coll Cardiol. 2008 Jan. 29; 51(4):449-55, which isincorporated herein by reference in its entirety).

Example 3: Elderly Carriers of the KIF6 719Arg Variant are at GreaterRisk for CHD and Also Benefited from Statin Therapy Whereas NoncarriersDid not Benefit: Results from the PROSPER Study

The Arg variant of the Trp719Arg polymorphism (rs20455/hCV3054799) inKIF6 is shown in Examples 1 and 2 above to be associated with greaterrisk for CHD, particularly MI, and greater benefit from statin therapy.The analysis described here in Example 3 relates to confirming whetherelderly carriers of this variant are at greater risk for coronaryevents, and whether elderly carriers receive significant benefit fromstatin therapy.

In this analysis, the KIF6 Trp719Arg polymorphism was analyzed insamples from the “Prospective Study of Pravastatin in the Elderly atRisk” (PROSPER) trial (PROSPER is described further in Shepherd et al.,Lancet. 2002 Nov. 23; 360(9346):1623-30). PROSPER was both a secondaryand primary trial of elderly men and women (ages 70-82). A substantialfraction of the patients in the PROSPER trial had an MI or othervascular disease prior to enrollment into the trial, and the rest of thepatients did not have a vascular event prior to enrollment. Since aninteraction has been observed between KIF6 carrier status and priorvascular events, groups with and without prior vascular events weregenotyped separately.

5752 patients were genotyped within the PROSPER trial, and Coxproportional hazards models were used to investigate (1) the risk forcoronary events in 719Arg carriers compared with noncarriers in aplacebo arm, and (2) the effect of statin therapy according to 719Argcarrier status in a pravastatin arm.

Table 8 shows the number of patients of the three genotypes and carriers(minor homozygote+heterozygote) in the placebo arm of the PROSPER trial.Among those in the placebo group with prior vascular disease, 719Argcarriers (59.0%) were at nominally greater risk for coronary eventscompared with noncarriers: hazard ratio=1.25 (95% CI 0.95 to 1.64; Table9). For heterozygotes compared with nonmcarriers, the hazard ratio=1.33(95% CI 1.01 to 1.77; Table 9).

Table 10 shows the number of patients of the three genotypes andcarriers (minor homozygote+heterozygote) in the placebo arm of thePROSPER trial. Table 11 shows the number of patients of the threegenotypes and carriers (minor homozygote+heterozygote) in thepravastatin arm of the PROSPER trial. To assess the effect ofpravastatin, risk estimates were used to compare the pravastatin armwith the placebo arm in subgroups defined by genotypes.

Among 719Arg carriers with prior vascular disease, a substantial andsignificant benefit from pravastatin therapy was observed (hazard ratio0.67, 95% CI 0.52 to 0.87; Table 12), whereas no significant benefit wasobserved in noncarriers (hazard ratio 0.92, 95% CI 0.68 to 1.25; Table12). The interaction between 719Arg carrier status and pravastatintreatment is shown in Table 13 (p=0.12).

Thus, elderly carriers of the KIF6 719Arg allele are at greater risk forCHD (e.g., MI) compared with noncarriers, and elderly carriers of theKIF6 719Arg allele receive significant benefit from statin therapywhereas noncarriers do not.

Example 4: Identification of SNPs in Linkage Disequilibrium with theKIF6 SNP—Analysis of 27 Tagging SNPs in CARE and WOSCOPS

To identify SNPs in linkage disequilibrium with the KIF6 Trp719Arg SNP(rs20455/hCV3054799) that may also be associated with CHD, 27 SNPs(which may be referred to herein as “tagging SNPs”) in the genomicregion around the KIF6 Trp719Arg SNP were analyzed in samples from boththe CARE and WOSCOPS trials (the CARE and WOSCOPS trials are describedfurther in Example 1) (Iakoubova et al., J Am Coll Cardiol. 2008 Jan.29; 51(4):435-43, particularly the Online Appendix, which isincorporated herein by reference in its entirety).

To test for association between CHD and other SNPs that may be inlinkage disequilibrium with the KIF6 Trp719Arg SNP, 27 tagging SNPs wereselected, including Trp719Arg, in genomic regions flanking the Trp719ArgSNP using pairwise tagging in Tagger (de Bakker et al., Nat Genet 2005;37:1217-23) as implemented in Haploview (Barrett et al., Bioinformatics2005; 21:263-5). These flanking genomic regions span 95.5 kb in the KIF6gene (from nucleotide positions 39,347,330 to 39,442,863 on chromosome 6(nucleotide positions based on HapMap release #19, October 2005; TheInternational HapMap Project. Nature 2003; 426:789-96) and contain 148SNPs that have allele frequencies greater than 2% in HapMap publicrelease #19. The 27 tagging SNPs (including the Trp7l9Arg SNP) tagged117 of these 148 SNPs with a mean r² of 0.93 (91% of SNPs were taggedwith r²>0.8; the minimum tagging r² was 0.7). The other 31 of the 148SNPs are less likely to be responsible for the observed association ofthe KIF6 Trp719Arg SNP and disease because they were not in stronglinkage disequilibrium with the Trp719Arg SNP (r²≤0.25). These 27tagging SNPs were genotyped in CARE and WOSCOPS samples and linkagedisequilibrium was assessed between KIF6 Trp719Arg and the other taggingSNPs using r² values from the placebo arms of both studies.

Based on this analysis, it was found that five of these 27 tagging SNPs(KIF6 Trp719Arg, as well as rs9471077, rs9394584, rs11755763, andrs9471080) were associated with recurrent MI in the placebo arm of CAREand with CHD in the placebo arm of WOSCOPS (p<0.15; meta-analysisp<0.05), with KIF6 Trp719Arg and rs9471077 being particularly stronglyassociated (Table 14). The risk estimate and the p-value were calculatedbased on the genetic model presented in Table 14 for each SNP. Thegenotype counts in both CARE and WOSCOPS are also presented in Table 14.The results of meta-analysis provided in Table 14 show the risk estimateand p-value from either the genotypic or genetic models (additive,dominant, recessive) that gave the lowest p-value in an analysis of CAREand WOSCOPS combined.

The SNPs in Table 14 (other than the KIF6 Trp719Arg SNP, which is shownelsewhere herein to be associated with drug response, particularlybenefit from statin treatment) were further analyzed to determinewhether individuals with increased risk of CHD will benefit frompravastatin treatment. Besides the KIF6 Trp719Arg SNP, four other SNPsin Table 14 (rs9471080/hCV29992177, rs9394584/hCV30225864,rs9471077/hCV3054813, and rs9462535/hCV3054808, which is described belowin the “Example 4—Supplemental Analysis” section below) were found to beassociated with benefit from pravastatin treatment in CARE and WOSCOPSsamples (this is shown in Table 22), in addition to their associationwith CHD risk (as shown in Table 14). Thus, these four SNPs areassociated with both CHD risk (particulary MI) and statin benefit.

rs9471077 is in strong linkage disequilibrium with the Trp719Arg SNP(r²=0.79 in placebo-treated patients), and the risk ratios for Trp719Argand rs9471077 were similar in the placebo arms of CARE and WOSCOPS.After adjusting for conventional risk factors, the hazard ratios were1.57 and 1.54 (p=0.01 and 0.02) in CARE for Trp719Arg and rs9471077,respectively, and the adjusted odds ratios were 1.59 and 1.46 (p=0.003and 0.01) in WOSCOPS for Trp719Arg and rs9471077, respectively. Nohaplotype in the KIF6 region was more significantly associated with bothrecurrent MI in CARE and with CHD in WOSCOPS than the KIF6 Trp719Arg SNPalone. The association of the rs9471077 SNP (an intronic SNP) with CHDis most likely explained by its linkage disequilibrium (r²=0.79) withthe missense Trp719Arg SNP, which may play a functional role in thepathogenesis of CHD and MI.

Example 4—Supplemental Analysis: Fine-Mapping Analysis of SNPs in theGenomic Region Around the KIF6 SNP

In the analysis described here, other SNPs around the KIF6 SNP wereanalyzed in CARE (the CARE trial is described further in Example 1) inorder to identify SNPs associated with CHD (particularly RMI) and/ordrug response, in addition to the SNPs described in Example 4 above.These markers were located by fine-mapping of the genomic region aroundthe KIF6 SNP rs20455. The genomic region around the KIF6 SNP rs20455that was analyzed was from nucleotide positions 39,335,279 to 39,679,743of chromosome 6 (nucleotide positions based on Hapmap position build36).

CARE was a secondary prevention trial. All the patients in the CAREtrial had MI within 10 months prior to enrollment into the trial. Duringthe 5 years of follow-up, 264 patients had experienced another MI and2649 patients had not developed another MI. In a placebo-treated group,150 patients among these 264 patients had experienced another MI and1290 patients among these 2649 patients had not developed another MI. Ina pravastatin-treated group, 114 patients had experienced another MI and1359 patients in this group had not developed another MI.

It was analyzed whether or not individuals with different genotypes incertain genetic polymorphisms were associated with recurrent MI (RMI) inthe placebo arm of CARE. For this analysis, the following were comparedusing Fisher's exact test (Table 15): the proportion of RMI events amongminor homozygote individuals compared with the proportion of RMI eventsamong major homozygote individuals; the proportion of RMI events amongheterozygote individuals compared with the proportion of RMI eventsamong major homozygote individuals; and the proportion of RMI eventsamong minor homozygote or heterozygote individuals compared with theproportion of RMI events among major homozygote individuals. Theassociation results for recurrent RMI and the genotype counts fordifferent genotypes in the placebo arm of CARE of six markers are shownin Table 15.

To determine association with drug response, Fisher's exact test wasused to assess the effect of pravastatin compared with placebo in CAREsubgroups defined by genotypes, as follows: the proportion of RMI eventsamong minor homozygote individuals treated with pravastatin comparedwith the proportion of RMI events among minor homozygote individualstreated with placebo; the proportion of RMI events among heterozygoteindividuals treated with pravastatin compared with the proportion of RMIevents among heterozygote individuals treated with placebo; theproportion of RMI events among major homozygote individuals treated withpravastatin compared with the proportion of RMI events among majorhomozygote individuals treated with placebo; and the proportion of RMIevents among minor homozygote or heterozygote individuals treated withpravastatin compared with the proportion of RMI events among minorhomozygote or heterozygote individuals treated with placebo. Estimatesof odds ratios and corresponding 95% confidence intervals werecalculated (Table 16). Deviation from Hardy-Weinberg expectations wereassessed using an exact test in the CARE cohort. Analysis in the CAREpopulation was performed using RMI as an endpoint. Genetic polymorphismsshowing a significant (p-value of <0.05) association with an effect ofpravastatin treatment on risk of RMI in any of the models or modesdescribed above are listed in Table 16.

In a further analysis, CARE and WOSCOPS samples were combined andlogistic regression models were used to calculate the risk, 95%confidence intervals (95% CI), and 2-sided p-values (see “Meta-Analysis”in Table 14) for the association of each SNP with CHD when adjusted foreach study. For example, the rs9462535 SNP (hCV3054808), which wasidentified by fine mapping of the genomic region surrounding theTrp719Arg SNP and analyzed in samples from the CARE trial as justdescribed (and presented in Tables 15-16), was further analyzed insamples from the WOSCOPS trial, and in a meta-analysis combining CAREand WOSCOPS. Based on this supplemental analysis in WOSCOPS and themeta-analysis combining CARE and WOSCOPS, the rs9462535 SNP (hCV3054808)was further confirmed to be associated with CHD (Table 14).

Example 5: Genetic Markers for Predisposition to Aneurysm or Dissection

The analysis described here in Example 5 relates to determining whetheror not the KIF6 SNP (hCV3054799/rs20455) is associated with aorticaneurysm and dissection.

To determine whether the KIF6 SNP (hCV3054799) is associated with aorticaneurysm or dissection, this SNP was analyzed using the following twoendpoints: (1) using aortic aneurysm or aortic dissection as anendpoint, which compared patients with aneurysm or dissection againstpatients without aneurysm or dissection (shown in Table 17), and (2)using aortic dissection as an endpoint, which compared patients withdissection against patients without dissection (shown in Table 18).

The study populations were as follows. 555 Caucasian patients withthoracic aortic aneurysm (TAA) or thoracic aortic dissection weregenotyped for the aneurysm or dissection endpoint analysis. 128Caucasian patients with thoracic aortic dissection were genotyped forthe dissection endpoint analysis. 180 patients without aneurysm ordissection were used as controls for both analyses. All samples werefrom the U.S. and Hungary (the U.S. samples may be referred to herein asthe “Yale University” samples).

Based on this analysis, the KIF6 SNP (hCV3054799) was found to beassociated (p-value ≤0.05) with aneurysm or dissection and withdissection only, and the risk allele in both instances was the sameallele that was previously associated with MI for this SNP (genotypecounts for both endpoints are shown in Tables 19 and 20). Also, thegenotypes of this SNP in controls did not deviate from the distributionsexpected under Hardy-Weinberg equilibrium (p-value >0.01).

Example 5—Supplemental Analysis

The analysis described here in this “Example 5—Supplemental Analysis”section relates to determining whether or not the KIF6 SNP(hCV3054799/rs20455) is associated with aortic aneurysm and dissectionindependently of CHD.

For this analysis, using the Yale University samples from Example 5above (which included individuals with thoracic aortic aneurysm ordissection, along with controls, as described above in Example 5),individuals who had a CHD event were removed from both case and controlsample sets. For this analysis, CHD was defined as MI, percutaneoustransluminal coronary angioplasty (PTCA), or coronary artery bypassgraft (CABG).

The KIF6 SNP was then analyzed in this sample set (which excludedindividuals with CHD) for association in the following two endpoints: 1)dissection only, and 2) aneurysm or dissection. The results of thisanalysis are presented in Table 21.

As shown in Table 21, the KIF6 SNP (hCV3054799/rs20455) is associatedwith dissection, as well as aneurysm or dissection, among patientswithout CHD. Therefore, the association of the KIF6 SNP(hCV3054799/rs20455) with aneurysm/dissection is independent of CHD.

Thus, the KIF6 SNP (hCV3054799/rs20455) is associated with risk foraortic aneurysm and aortic dissection (as shown here in Example 5 andthe “Example 5—Supplemental Analysis” section), as well as risk forother coronary events such as CHD (including MI). Therefore, this SNPhas been shown to be associated with multiple different coronary events,and is therefore expected to have similar utilities in other coronaryevents. Consequently, the KIF6 SNP (hCV3054799/rs20455), as well as theother SNPs disclosed herein, is broadly useful with respect to the fullspectrum of coronary events. Furthermore, the KIF6 SNP(hCV3054799/rs20455) has also been associated with other cardiovascularevents such as stroke (see, e.g., U.S. provisional patent application61/066,584, Luke et al., filed Feb. 20, 2008). Therefore, this SNP hasbeen shown to be associated with multiple different cardiovascularevents, and is therefore expected to have similar utilities in othercardiovascular events. Consequently, the KIF6 SNP (hCV3054799/rs20455),as well as the other SNPs disclosed herein, is broadly useful withrespect to the full spectrum of cardiovascular events. Moreover, thisSNP has been specifically shown to be associated with benefit fromstatin treatment for reduction of MI, unstable angina,revascularization, and stroke events (see, e.g., Example 2). The KIF6SNP (hCV3054799/rs20455), as well as the other SNPs disclosed herein, isalso particularly useful for determining an individual's risk forvulnerable plaque.

Example 6: Calculated LD SNPs Associated with CHD and Drug Response

Another investigation was conducted to identify additional SNPs that arecalculated to be in linkage disequilibrium (LD) with certain“interrogated SNPs” that have been found to be associated with CHD(particularly MI), aneurysm/dissection, and/or drug response(particularly statin response), as described herein and shown in thetables. The interrogated SNPs are shown in column 1 (which indicates thehCV identification numbers of each interrogated SNP) and column 2 (whichindicates the public rs identification numbers of each interrogated SNP)of Table 4. The methodology is described earlier in the instantapplication. To summarize briefly, the power threshold (T) was set at anappropriate level, such as 51%, for detecting disease association usingLD markers. This power threshold is based on equation (31) above, whichincorporates allele frequency data from previous disease associationstudies, the predicted error rate for not detecting trulydisease-associated markers, and a significance level of 0.05. Using thispower calculation and the sample size, a threshold level of LD, or r²value, was derived for each interrogated SNP (r₁₂, equations (32) and(33) above). The threshold value r² is the minimum value of linkagedisequilibrium between the interrogated SNP and its LD SNPs possiblesuch that the non-interrogated SNP still retains a power greater orequal to T for detecting disease association.

Based on the above methodology, LD SNPs were found for the interrogatedSNPs. Several exemplary LD SNPs for the interrogated SNPs are listed inTable 4; each LD SNP is associated with its respective interrogated SNP.Also shown are the public SNP IDs (rs numbers) for the interrogated andLD SNPs, when available, and the threshold r² value and the power usedto determine this, and the r² value of linkage disequilibrium betweenthe interrogated SNP and its corresponding LD SNP. As an example inTable 4, the interrogated SNP rs20455 (hCV3054799) (the KIF6 SNP whichis shown herein to be associated with CHD, particularly MI, as well asaneurysm/dissection and drug response, particularly statin response) wascalculated to be in LD with rs6924090 (hCV29161261) at an r² value of 1,based on a 51% power calculation, thus establishing the latter SNP as amarker associated with CHD, aneurysm/dissection, or drug response aswell.

All publications and patents cited in this specification are hereinincorporated by reference in their entirety. Modifications andvariations of the described compositions, methods and systems of theinvention will be apparent to those skilled in the art without departingfrom the scope and spirit of the invention. Although the invention hasbeen described in connection with specific preferred embodiments andcertain working examples, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments.Indeed, various modifications of the above-described modes for carryingout the invention that are obvious to those skilled in the field ofmolecular biology, genetics and related fields are intended to be withinthe scope of the following claims.

TABLE 1 Gene Number: 1 Celera Gene: hCG1647070-84000313730920Celera Transcript: hCT1647197-84000313730921Public Transcript Accession: NM_145027 Celera Protein:hCP1617236-197000069366336 Public Protein Accession: NP_659464Gene Symbol: KIF6 Protein Name: kinesin family member 6Celera Genomic Axis: GA_x5YUV32W6W6 (12311520..12426711) Chromosome: 6OMIM NUMBER: OMIM Information: Transcript Sequence (SEQ ID NO: 1):Protein Sequence (SEQ ID NO: 2): SNP Information Context (SEQ ID NO: 3):GTGGGCAGAGGAGGCCACCAACCTGCAGGTAAATTCTCCAGCAGTGAATTCACTCGATCACACGAAGCCATTTCTCCAGACATCTGACTCCCAGCATGAA YGGTCCCAACTCCTCTCTAACAAAAGTTCTGGAGGCTGGGAAGTCCAAGATCAAGGCACTGGCAGATTCGATGTCTGTGATGTGAATGCCAGGAAAATCCT Celera SNP ID: hCV3054799 Public SNP ID: rs20455SNP in Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 694SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele,Count): caucasian (T,77|C,43) SNP Type:Missense Mutation Protein Coding:SEQ ID NO: 2, at position 170, (W,TGG) (R,CGG)

TABLE 2 Gene Number: 1 Celera Gene: hCG1647070-84000313730920Gene Symbol: KIF6 Protein Name: kinesin family member 6Celera Genomic Axis: GA_x5YUV32W6W6 (12311520..12426711) Chromosome: 6OMIM NUMBER: OMIM Information: Genomic Sequence (SEQ ID NO: 4):SNP Information Context (SEQ ID NO: 10):ACAGGAATAGGTTAAACAGAAAGGTAGGGAGCCTTTTCTGGGAACTCTAACACCTCCGGTGAGTTCTCACCTTACCTTTTGTTAGAGAGGAGTTGGGACC RTTCATGCTGGGAGTCAGATGTCTGGAGAAATGGCTTCGTGTGATCGAGTGAATTCACTGCTGGAGAATTTACCTGTTGGCCCCAGAAGGAGTTTCACAGT Celera SNP ID: hCV3054799 Public SNP ID: rs20455SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 31149SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): caucasian (A,77|G,43) SNP Type:MISSENSE MUTATION Context (SEQ ID NO: 11):GCTCCACTGATCCCAGGTGGATTGCTGGAAAGTCTTTTCAAAACATTGCATCAATTTCTCCCATTTGCAGAGGCCAGTGAACTCTGGGAAGGTGCACTGC YGTCAAGCATGTGTCCATATCAAAGGCTGGGCTTCCATTAGGGGATGTTCGGAGCAAAAGGCCCCTTGGCCAGTTGCTGCACACACTTTGCATATGCTCTG Celera SNP ID: hCV792699 Public SNP ID: rs728218SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 7857SNP Source: dbSNP; Celera Population (Allele, Count):caucasian (C,55|T,65) SNP Type: INTRON Context (SEQ ID NO: 12):TTTCAACATCCAACATTCACAGCCAACCTCTCTACACCTGCTCTGCCTCGGAGCCCTGGCAGTCCCTGGACACGTGTTATGGAAGGAACACTGTCTCCCC SACATGCTCACATGGCCCAAATCCCCACAAGTCCCCTTTTTGCCAAGCTCCACGTCCTTTGCCTCTTCCCATCACCCAATACCCAACCTGCCATCATTGTC Celera SNP ID: hCV1650850 Public SNP ID: rs35268572SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 4809SNP Source: Celera Population (Allele, Count): no pop (C,-|G,-)SNP Type: INTRON Context (SEQ ID NO: 13):TCTAATTTAATTTTAATAACATCTTTGTTTAAAAACGGCTCCCCACATTCCTGGAGTACTAACAGTTTATGCTTTTATGGACTGAGCCAGCTCAGCACAC MACTGGGAATGGCTTATCATCATCCATGAATGATTTCTTCCAAATGGTGCCTCTCACATTACCACTAAATCTTTGTTCCTTTGGGATATGGGATTGCCTTT Celera SNP ID: hCV3054766 Public SNP ID: rs9394587SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 54872SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (C,57|A,63) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 14):CAACTAATGATTCATTTGCTGAATACCCACTCTGGGCCTCCTTGGGGCTCAGCTGTCTCACACAACCATAGATCACTTCAGCCTCACCTTGTTTGAGAAG WCAAAGTGTCTATTCTTACGGAGATTGATGGTGTTCATAGCTCAATTACCACAATGGTCAGCAGCTCAGAGGCAAAGATTCTGGCTTCCCAATCAGACCAT Celera SNP ID: hCV3054789 Public SNP ID: rs4711595SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 42930SNP Source: dbSNP; Celera; HGBASE Population (Allele, Count):caucasian (A,33|T,87) SNP Type: INTRON Context (SEQ ID NO: 15):GTCTTTGAAGCCAAAGGAAAAATGAGAGACAGGGCTTTCTACTCGCTGAGCAGGATATTGCTACCAGTAGAAGCTACCCAAGAGATCAGAAAAGAGGGTA SAGAAATAGCCAGGGGTTCTGAGCCTCACAGCTGAAAGGAGAGCTTATTCTCATGGGGCAGATACACAAGGGCTCAGCACAGAGCCAGAGCAATGATTGAG Celera SNP ID: hCV3054805 Public SNP ID: rs2894424SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 25606SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (C,67|G,51) SNP Type: INTRON Context (SEQ ID NO: 16):AGCAGTGGAGAGACTTTCCACGAGGTGCCCTTCATGGTGGGAAAGCAGAGATCCCTGTGCTGGGTCTAGTGAGGACCGATGTAGGACCAGAGGTAGCCAC MAGGTGGCAGGCTCTGCACGCTTTTCTTCAGAGAACAGTAACCAATTCTCAAGGCTCCTGCTGAGTGGTTCCTGGTGCAGCCTGGAGAAGGGAAGGAGAAA Celera SNP ID: hCV3054808 Public SNP ID: rs9462535SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 21875SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,50|C,74) SNP Type: INTRON Context (SEQ ID NO: 17):GGTAGATGTCATCGTCTCCATTTTATACATGAGAAAACTGAGGCTTAGACAGATTAAAGAAATTCTAAAGTTATCCAGCTGGTAAGTGGCAGAATCGGGA RCTACTCAGGATTCTTTGAGGCTTCAGAACCTGTGCTCTCAGCCACAATGCCTTCTAACTGGGCTTGACTCTGTGGCATTCTAGGAACACACGCTGGCCTA Celera SNP ID: hCV3054809 Public SNP ID: rs11755763SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 21059SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,51|G,69) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 18):GGAGGAATGATGGTTGGTTTCTATGGATTTGTTACAGGGGAAGGGATATCTCAGCTCAAAGGATATCCTGCGTATCCAAGCCTTCCTCCACTTGTGCCCC RCACACTGTCCCCTCTACTTTCTCAAGGAAGTTTTTCCTGCAGCTCTGCTCCCCTCTCCCACCACAGCATCAGTTTCCCTCTCTATGCATGTTTCAGCACG Celera SNP ID: hCV3054813 Public SNP ID: rs9471077SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 14825SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,73|G,47) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 19):TCAGAAACTGCATCTTTCTTTTTTTTAAGGAGCAGGATTCCTCTTGCACATGAAATCTTTCCCAGAGCCCCAATCTGAAGCCTACTTAAGAGTGGAGCTC WGGTTGAAGTAGGGGCAGAGGGCTCCCATTTCCACCAGCCCAGAGAGTGTGATTTCAAGAGCCCTTACCCGTAATTCTGAAATGGATGCCCTTGTCTAAGT Celera SNP ID: hCV3054822 Public SNP ID: rs11751357SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 2345SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (T,90|A,28) SNP Type: INTRON Context (SEQ ID NO: 20):GTAGAGGCTGCGGTCACTCCCCTCGTCAATGCTGGTTCCTGTTCCTGAGGCCGAGAGAACTCCTGACAGCAGAGTGGGCATATCTTGGTAGTTGCAGCTT YTCAAGACAGTGTGGCCCAGTGGGGAGAGAGCAGAAAACCTGGGTTATGCTGGCTCTGCCATTTATCAGCTGTGTAACCTTGGGCAAGTGATACAACCTCT Celera SNP ID: hCV15876373 Public SNP ID: rs2281686SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 14290SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):caucasian (T,105|C,15) SNP Type: INTRON Context (SEQ ID NO: 21):TCCAAAAATAGCCTTATGGCTGATACCTAATTGCATTTCTAACAGAGCTATTCTTCATGTGCAGATAACAGTCTCTGTAACCTGCTGGATCTTGCAGCTT YATGGGTTTTGGCAAAAAAAGGAGTTGAGGGGGATTGCAGAATTCACTCAGCATGCAGCTTGCTGTCATTACCACGGTGATAAATTTGCTGGTTTTGGCCT Celera SNP ID: hCV31340487 Public SNP ID:rs12175497 SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic:62509 SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (T,106|C,12) SNP Type: HUMAN-MOUSE SYNTENIC REGION; INTRONContext (SEQ ID NO: 22):TTCCCCCAGTGCTGTGTTCAGACTCCATGAGTCACTCCATGAGGGTGACTCAGTGCCTCGCATGTTTGCTGGCCTTGCCTTCTTTGAAAGTCATCAGACA YGATAAACTGAAGGAAGTATCTTAATATGAAACCGACAATGGTAGGACTTTCAATGGACAAACAATTCCTTTTTAAAAAGTTTCAGAAATGGGCCCAGGTA Celera SNP ID: hCV30388472 Public SNP ID: rs9357303SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 39408SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (T,62|C,52) SNP Type: INTRON Context (SEQ ID NO: 23):TATCCAAATATTCTTCTCCATTGTCCTGCCGCGTGGCCACTTGCTATCACACTGGTTATTGCTTGGCTATGTCCTTGGCAAATCATCTTCTCTGGCTCTC RGTTTTCTTGTCCTTAAAATGAAGGGATCAGCCTGTCAGATAATCAGTAAGCATTCTGCCAGCCAGAAAAGGGATCTGATTGTGCGTATTTTAGCACTTCC Celera SNP ID: hCV30225864 Public SNP ID: rs9394584SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 33000SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (A,74|G,36) SNP Type: INTRON Context (SEQ ID NO: 24):AGCAGGCTGGCGGCCAAGCAAGGCGAGTACAGGACCAAGGCCGGCTCTCAGTTGCGGCGCTCCATCCATGCACAAACCTCTTCCTGCCCAAACTGCACAC RGCTGGTGGAGAAGCTGAGTGCAGGCGCCACAGGGCAGGCATCAGTCATTATACATCGAATCTGCCAGCCCATACCATCACGGTGGGGGCGCCTTTCTGGC Celera SNP ID: hCV30478067 Public SNP ID: rs9471078SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 16718SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (G,108|A,12) SNP Type: INTRON Context (SEQ ID NO: 25):ATTATTAACATTTTGTATTAGTGTGATAAATTTGTTATAACTGGTGAATGAATATAGATACATTATTATGAACTAAAGTCCATGGTTTATGCAGGGGTTC RCTCTTTGTGCTGTACAGCTCTATGGATTTTGACAAATGCATGACATCATCTATGCAACATTACAATATCATACAGAATAGTTTCACTGCCCCCAAAATTC Celera SNP ID: hCV29992177 Public SNP ID: rs9471080SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 26159SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (A,94|G,24) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 26):ATGGCAGTAGGTCTACTGGCTGTCAGAGTGAGGGACTGAAGGGGTGTGCACTCCAACCAACTTGAAAGCCACTGTCTTGAGTATCTACGACTAATTAAAC RGTAAAAGGAATTAATCCTGCTGGATCATATGGCTTATCAAGAGACATGAGAGCCACAGGAATAGGTTAAACAGAAAGGTAGGGAGCCTTTTCTGGGAACT Celera SNP ID: hCV2946524 Public SNP ID: rs20456SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 30994Related Interrogated SNP: hCV30225864 (Power = .51) SNP Source: AppleraPopulation (Allele, Count): caucasian (A,23|G,15) african american(A,11|G,27) total (A,34|G,42) SNP Type: INTRON SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (A,67|G,53) SNP Type: INTRON Context (SEQ ID NO: 27):CTGGGCTTCCATTAGGGGATGTTCGGAGCAAAAGGCCCCTTGGCCAGTTGCTGCACACACTTTGCATATGCTCTGGACACCAGTGGCCCCAGATCCCATG YTGTGTGTTTTTCTGTCTTCATTTCCTTTCCTGTCTTAGTGATTGCCCCAGGAGGCTGGTTCACACCCCGCATGGGGCCATGCCACACATCTCTGTCAGTA Celera SNP ID: hCV792698 Public SNP ID: rs728217SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 7983Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,63|C,55) SNP Type: INTRON Context (SEQ ID NO: 28):TCAGTCAGAGCCTGGGGGAAGTCAGAGTGACACCAGCCTGAGAAACACATCTGGGTTCTGGCTCGTCTACTCATGAACTGAAGGACCGTTTACTGAACAG YGACTCTGTGCTTGGGACACAGCAATGAGCAAGACAAACAGGTCCCTGTTGCATTGGAGCTCTTAGTATTATGGGGGGTTGCAGGTATTTCAAAAATAGGC Celera SNP ID: hCV11606396 Public SNP ID: rs1887716SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 8897Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (C,69|T,51)SNP Type: INTRON Context (SEQ ID NO: 29):GATTGGCCTTCAGGATGCCCTGCATTCCACTGCCTTGCCTGTGGCTGGGACATCCTGCCTGGACCTGTCATGGCCATTTCTGGGCTTCCAAACCAGAGCA YGGGCCAAGGGAGAGAGCTGGCAAATCGTTAAAAATAAAAATATTCCCCCCACATTCCACTGGTGTGAGCATCCTCTGACATTATATTTTGATGGTGCTAT Celera SNP ID: hCV27495641 Public SNP ID: rs3823213SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 9935Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,89|T,31)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 30):TCTAGAAAGGGGTTAACCTCATTTCCTCAGACATAAAAACTGTCCTTGGCAGTTGGAAACAGCAGAGTTGACTCCACGGATGACTGATGCCCCTTACGGG KGTTATATACCTGTCCACGCCTGCCCCTGGCAGGGATTTAAACATTCCATGCTGTTCCATGAATCCTAAATCAAATAGATTCATCCTGGCCCTTGGTGAAG Celera SNP ID: hCV27505675 Public SNP ID: rs3818308SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 13597Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,84|G,36) SNP Type: INTRON Context (SEQ ID NO: 31):ATGTCCTTAGACCCTGCAGGGCAGATGGCTCCCTGGAGACACAGCTGTTCAGGCACTGCCTCCAGGTCATCCTGGCCAAGAGGCTGATGGTGAAAGATGT RGTCTGGGAGATCAGGATTGGCCTTCAGGATGCCCTGCATTCCACTGCCTTGCCTGTGGCTGGGACATCCTGCCTGGACCTGTCATGGCCATTTCTGGGCT Celera SNP ID: hCV29161257 Public SNP ID: rs6904582SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 9820Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,69|A,51)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 32):GACAGAGAGCCTGAGGGGTGAGGCTGCTCAGGGAACAGGTGAGCAGGCAGCTGCAGCCCTCCAGGTTCGGCCACAGGAACCTGGTACTGGGTGACGAGTG KTAGCTTGGTTGGCTTGATATTGCTGTGGAAGAAAGGGTAATTCTTGGTGATACATTGAATGGCCAGCTAGTGCGGAGGAAGAGATTGGAAATAATTCACG Celera SNP ID: hCV29161258 Public SNP ID: rs6901022SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 12146Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,81|G,39)SNP Type: INTRON Context (SEQ ID NO: 33):TGGCAGGAGGCGTGCTTCCTCGGTGCTACCCCCTGGGTTGTGTGGTTGGAAAGAGACAATAACATGGTTGTGGGGAAGTAGAGTCCCTGCTGGTCATCCC RTCATGTAGGGAGACTGGCTCTGGGCCATCCTCATGTGGTGTTTTTGGAGGCTACCTGGATCCTGGCTAGGACGAAGAGCTCCCCTGTGTCTCAGTAGGCG Celera SNP ID: hCV29161261 Public SNP ID: rs6924090SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 30652Related Interrogated SNP: hCV30225864 (Power = .6)Related Interrogated SNP: hCV3054799 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,76|G,42)SNP Type: INTRON Context (SEQ ID NO: 34):CAGGTGATCAGCCTTCTGAAGTGCTGGGATTACAGGCATGAGCCACCGTGCCCAGCCTGATTCTATTTGTACAAAAACATATGGATATATATGCATAGAA RTCAAGGTAAAAGAATATAATCAAACATGTTAATATCAATTACATTTAAGTAGAGGAATTATGGTGATTTTTACTTTCTTCTTTGTGTTTTTCTGCCTAGT Celera SNP ID: hCV29576755 Public SNP ID: rs6899653SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 33779Related Interrogated SNP: hCV30225864 (Power = .7)Related Interrogated SNP: hCV29992177 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,83|G,37)SNP Type: INTRON; REPEATS Context (SEQ ID NO: 35):AATTTGGTCTTCCTCTGGTTCTACAGACTTTACAGAGGGCTTACTATGTTCCATTGAACTGTGAGGGCCAGGAGTGGACCAGAGATGCTGGCCCCTGTCC YGATGGGATTCAGTCAGAGCCTGGGGGAAGTCAGAGTGACACCAGCCTGAGAAACACATCTGGGTTCTGGCTCGTCTACTCATGAACTGAAGGACCGTTTA Celera SNP ID: hCV30532403 Public SNP ID: rs7754225SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 8788Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,65|T,55)SNP Type: INTRON Context (SEQ ID NO: 36):ACACAGGATGTTGTGTACCTTGTCATGTACTTATTTGCCATCTGTATCTCTTCTTTGGTGAAGTGGCTGTTCAGATCTTTTGCCCACTTTTAAACTGAGT KGTTTATTTTCTTATTGTTGAATTTTTAGAGCTCTTTGTATACTTCAGATACAAGTCCTTTATCAGATATATGTTTTGCAAATATTTTCTCCCAGTCTGTA Celera SNP ID: hCV30280062 Public SNP ID: rs7772430SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 27267Related Interrogated SNP: hCV30225864 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,65|T,51)SNP Type: INTRON; REPEATS Context (SEQ ID NO: 37):TGAGGTATGGTCGCACCACTGCACCCCAGCCTGGCTGACAGAGACCCCCCCCATCTCAAAAAATAAATAAAAGAAAGTAAAAATAAAAGAAAATAAAAGT YAGTAGACTCTACCCAGCTCTAGAGGGCTGAGGGCACTAAGGCATGCCAAGAATACTGCTGCTGCTACATAGGGGACTGGGGCAAATGCCATGCCATCTTC Celera SNP ID: hCV30190183 Public SNP ID: rs7774046SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 8497Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source: dbSNP Population (Allele, Count): caucasian (T,65|C,55) SNP Type: INTRONContext (SEQ ID NO: 38):AAAGAAAGTAAAAATAAAAGAAAATAAAAGTTAGTAGACTCTACCCAGCTCTAGAGGGCTGAGGGCACTAAGGCATGCCAAGAATACTGCTGCTGCTACA YAGGGGACTGGGGCAAATGCCATGCCATCTTCAGGGCTCTTGAGAGTGTGTGTGTGTATGTGTGTGTGTGTGTGCAGTTACATGTGTGTTCCATGGACTCT Celera SNP ID: hCV30082078 Public SNP ID: rs7774204SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 8566Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,65|C,55)SNP Type: INTRON Context (SEQ ID NO: 39):TGGCTGTTGGAAACATGAACTCTTCCCAACACAGTGTTATCTCAGGAAATTATTCCACCTGCTTCCTCCTGGTGGTTCTTTCCCCTGCCTTGGGTAATTT STTCACATGCAGATGTTGATCGGTAGTTAGCTGAAGACTCAAGGGTAACCCTCTGAAGATCTCCAGAGCATGCTCTCTCTCTTTCTCTCTCTTTTTTCTCC Celera SNP ID: hCV30586596 Public SNP ID: rs9369112SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 6540Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,88|G,32)SNP Type: INTRON Context (SEQ ID NO: 40):CAAATGCCATGCCATCTTCAGGGCTCTTGAGAGTGTGTGTGTGTATGTGTGTGTGTGTGTGCAGTTACATGTGTGTTCCATGGACTCTTGGGGAGGCTTC YAGAATCAGAATTTGGTCTTCCTCTGGTTCTACAGACTTTACAGAGGGCTTACTATGTTCCATTGAACTGTGAGGGCCAGGAGTGGACCAGAGATGCTGGC Celera SNP ID: hCV29902034 Public SNP ID: rs9380848SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 8679Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,89|C,31)SNP Type: INTRON Context (SEQ ID NO: 41):CCCCCAGGCAGCTATGTTTTTCCCTGTGGAAGTGGGGAGTGTCAGCCCAAATCCTCCCAAGTGGCTGGGTGAAGGTTGTGAGGCCCAAGGTACCCACACT RCCCTCTCTCAAGCTCTCAGCAGAGCCCCTGGGAGCTGCCCACTGTTCTCTGGGTGCTATGATGTCCTTAGACCCTGCAGGGCAGATGGCTCCCTGGAGAC Celera SNP ID: hCV29937959 Public SNP ID: rs9462531SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 9659Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,77|A,41)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 42):TGGCCATGGCTGAAACTCACTGCTTTTGTCTCTCTAGTACAAGGACTGGCAGGGCAAGAGCTGGGGGCCCGTGGGCACGTGGCTGCTGATGAGATCTGGG STCTGATGTTTCTGCTGCACTGTTGAAATGCAGCCTGGGCCAGGATTGTGAACGCTGCCGGTGGTAGGGAGCATGGAGTCTGAGCCATCTCCCACCCAGGA Celera SNP ID: hCV30478066 Public SNP ID: rs9462533SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 12662Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,76|G,44)SNP Type: INTRON Context (SEQ ID NO: 43):AGAGCAATGATTGAGGAAGCTGAATCCTCCTCGTTGTGTTTTTCAGATGTGCTGTGTGGAGTCCTGGAGTTTCAGCGAGAGGGCTCCGTGTGTGGAAGGT SCAGGTATACAGGGGTTGGAATTCAAATTTACTGGCCTCTAGAGGTTGGCAGGTGCCCAGGTGAATGCATGGAGTGGGCCAGGTGCAGGGCACAAATGCTA Celera SNP ID: hCV29703356 Public SNP ID: rs9471079SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic: 25792Related Interrogated SNP: hCV29992177 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,94|C,24)SNP Type: INTRON Context (SEQ ID NO: 44):TCAGTTTTTCACAAACCACCCAAGCCCAATAAGACTTCACCTGGCTGGGGTTTAGGATAGAGTCTTTCTCAGAAGCATGTTCAGTTTAATGGGGGACTTC YGAAAACCCTAGGGCCACAAAAGCCACAGAAAGGGCAACATAATGGTGGACTTTGGGGGAGATCTCAGCTCAAGAGGCCCACAGACTGTGCTGTAGGAACT Celera SNP ID: hDV70715992 Public SNP ID:rs16891930 SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic:594 Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,95|C,23)SNP Type: INTRON Context (SEQ ID NO: 45):GGACCCCGTGTCAACCTGTCTTTGGCTTCCTTTGTGGCCCCGTGGTCACTGAAAAGCCAGAATGAATATTCTTCCTTTCGGAATAAAAATTGAGCTGTGG RAGTTTTGTTTGCTTTGATGAATTACTTCCAGGCTGCTGTTTATTTGGAGAGCAAAGCTCCCCAGCTGCAGGGTGGGTAGAGGCTGCGGTCACTCCCCTCG Celera SNP ID: hDV70716012 Public SNP ID:rs16891961 SNP in Genomic Sequence: SEQ ID NO: 4 SNP Position Genomic:14114 Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,83|G,35)SNP Type: INTRON Gene Number: 2 Celera Gene: hCG33195-84000313730962Gene Symbol: KIF6 Protein Name: kinesin family member 6Celera Genomic Axis: GA_x5YUV32W6W6 (12492363..12669871) Chromosome: 6OMIM NUMBER: OMIM Information: Genomic Sequence (SEQ ID NO: 5):SNP Information Context (SEQ ID NO: 46):ACAGGAATAGGTTAAACAGAAAGGTAGGGAGCCTTTTCTGGGAACTCTAACACCTCCGGTGAGTTCTCACCTTACCTTTTGTTAGAGAGGAGTTGGGACC RTTCATGCTGGGAGTCAGATGTCTGGAGAAATGGCTTCGTGTGATCGAGTGAATTCACTGCTGGAGAATTTACCTGTTGGCCCCAGAAGGAGTTTCACAGT Celera SNP ID: hCV3054799 Public SNP ID: rs20455SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 149694SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): caucasian (A,77|G,43) SNP Type:MISSENSE MUTATION Context (SEQ ID NO: 47):TCTAATTTAATTTTAATAACATCTTTGTTTAAAAACGGCTCCCCACATTCCTGGAGTACTAACAGTTTATGCTTTTATGGACTGAGCCAGCTCAGCACAC MACTGGGAATGGCTTATCATCATCCATGAATGATTTCTTCCAAATGGTGCCTCTCACATTACCACTAAATCTTTGTTCCTTTGGGATATGGGATTGCCTTT Celera SNP ID: hCV3054766 Public SNP ID: rs9394587SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 125971SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (C,57|A,63) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 48):CAACTAATGATTCATTTGCTGAATACCCACTCTGGGCCTCCTTGGGGCTCAGCTGTCTCACACAACCATAGATCACTTCAGCCTCACCTTGTTTGAGAAG WCAAAGTGTCTATTCTTACGGAGATTGATGGTGTTCATAGCTCAATTACCACAATGGTCAGCAGCTCAGAGGCAAAGATTCTGGCTTCCCAATCAGACCAT Celera SNP ID: hCV3054789 Public SNP ID: rs4711595SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 137913SNP Source: dbSNP; Celera; HGBASE Population (Allele, Count):caucasian (A,33|T,87) SNP Type: INTRON Context (SEQ ID NO: 49):GTCTTTGAAGCCAAAGGAAAAATGAGAGACAGGGCTTTCTACTCGCTGAGCAGGATATTGCTACCAGTAGAAGCTACCCAAGAGATCAGAAAAGAGGGTA SAGAAATAGCCAGGGGTTCTGAGCCTCACAGCTGAAAGGAGAGCTTATTCTCATGGGGCAGATACACAAGGGCTCAGCACAGAGCCAGAGCAATGATTGAG Celera SNP ID: hCV3054805 Public SNP ID: rs2894424SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 155237SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (C,67|G,51) SNP Type: INTRON Context (SEQ ID NO: 50):AGCAGTGGAGAGACTTTCCACGAGGTGCCCTTCATGGTGGGAAAGCAGAGATCCCTGTGCTGGGTCTAGTGAGGACCGATGTAGGACCAGAGGTAGCCAC MAGGTGGCAGGCTCTGCACGCTTTTCTTCAGAGAACAGTAACCAATTCTCAAGGCTCCTGCTGAGTGGTTCCTGGTGCAGCCTGGAGAAGGGAAGGAGAAA Celera SNP ID: hCV3054808 Public SNP ID: rs9462535SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 158968SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,50|C,74) SNP Type: INTRON Context (SEQ ID NO: 51):GGTAGATGTCATCGTCTCCATTTTATACATGAGAAAACTGAGGCTTAGACAGATTAAAGAAATTCTAAAGTTATCCAGCTGGTAAGTGGCAGAATCGGGA RCTACTCAGGATTCTTTGAGGCTTCAGAACCTGTGCTCTCAGCCACAATGCCTTCTAACTGGGCTTGACTCTGTGGCATTCTAGGAACACACGCTGGCCTA Celera SNP ID: hCV3054809 Public SNP ID: rs11755763SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 159784SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,51|G,69) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 52):GGAGGAATGATGGTTGGTTTCTATGGATTTGTTACAGGGGAAGGGATATCTCAGCTCAAAGGATATCCTGCGTATCCAAGCCTTCCTCCACTTGTGCCCC RCACACTGTCCCCTCTACTTTCTCAAGGAAGTTTTTCCTGCAGCTCTGCTCCCCTCTCCCACCACAGCATCAGTTTCCCTCTCTATGCATGTTTCAGCACG Celera SNP ID: hCV3054813 Public SNP ID: rs9471077SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 166018SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (A,73|G,47) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 53):GTAGAGGCTGCGGTCACTCCCCTCGTCAATGCTGGTTCCTGTTCCTGAGGCCGAGAGAACTCCTGACAGCAGAGTGGGCATATCTTGGTAGTTGCAGCTT YTCAAGACAGTGTGGCCCAGTGGGGAGAGAGCAGAAAACCTGGGTTATGCTGGCTCTGCCATTTATCAGCTGTGTAACCTTGGGCAAGTGATACAACCTCT Celera SNP ID: hCV15876373 Public SNP ID: rs2281686SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 166553SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):caucasian (T,105|C,15) SNP Type: INTRON Context (SEQ ID NO: 54):TTTTTCAATCACTTTGTTATCTTGGAGTAAAATATCTCGACAGGAATTTCCACTAATCTAGAATAGATCAAATAAAGGAAATCTCTTTTCGATTGAACAG SACATTATAAAGCATATGCCTGAGACTCCTTAAAACAAACCAACTAAGAACAACAATAGCAACCACAGGATCTAGAATTCAGCTTTCCACTTCAGTTCTCC Celera SNP ID: hCV32202303 Public SNP ID:rs11751690 SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic:96995 SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (G,106|C,12) SNP Type: INTRON Context (SEQ ID NO: 55):TCCAAAAATAGCCTTATGGCTGATACCTAATTGCATTTCTAACAGAGCTATTCTTCATGTGCAGATAACAGTCTCTGTAACCTGCTGGATCTTGCAGCTT YATGGGTTTTGGCAAAAAAAGGAGTTGAGGGGGATTGCAGAATTCACTCAGCATGCAGCTTGCTGTCATTACCACGGTGATAAATTTGCTGGTTTTGGCCT Celera SNP ID: hCV31340487 Public SNP ID:rs12175497 SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic:118334 SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (T,106|C,12) SNP Type: HUMAN-MOUSE SYNTENIC REGION; INTRONContext (SEQ ID NO: 56):TTCCCCCAGTGCTGTGTTCAGACTCCATGAGTCACTCCATGAGGGTGACTCAGTGCCTCGCATGTTTGCTGGCCTTGCCTTCTTTGAAAGTCATCAGACA YGATAAACTGAAGGAAGTATCTTAATATGAAACCGACAATGGTAGGACTTTCAATGGACAAACAATTCCTTTTTAAAAAGTTTCAGAAATGGGCCCAGGTA Celera SNP ID: hCV30388472 Public SNP ID: rs9357303SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 141435SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (T,62|C,52) SNP Type: INTRON Context (SEQ ID NO: 57):TATCCAAATATTCTTCTCCATTGTCCTGCCGCGTGGCCACTTGCTATCACACTGGTTATTGCTTGGCTATGTCCTTGGCAAATCATCTTCTCTGGCTCTC RGTTTTCTTGTCCTTAAAATGAAGGGATCAGCCTGTCAGATAATCAGTAAGCATTCTGCCAGCCAGAAAAGGGATCTGATTGTGCGTATTTTAGCACTTCC Celera SNP ID: hCV30225864 Public SNP ID: rs9394584SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 147843SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (A,74|G,36) SNP Type: INTRON Context (SEQ ID NO: 58):AGCAGGCTGGCGGCCAAGCAAGGCGAGTACAGGACCAAGGCCGGCTCTCAGTTGCGGCGCTCCATCCATGCACAAACCTCTTCCTGCCCAAACTGCACAC RGCTGGTGGAGAAGCTGAGTGCAGGCGCCACAGGGCAGGCATCAGTCATTATACATCGAATCTGCCAGCCCATACCATCACGGTGGGGGCGCCTTTCTGGC Celera SNP ID: hCV30478067 Public SNP ID: rs9471078SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 164125SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (G,108|A,12) SNP Type: INTRON Context (SEQ ID NO: 59):ATTATTAACATTTTGTATTAGTGTGATAAATTTGTTATAACTGGTGAATGAATATAGATACATTATTATGAACTAAAGTCCATGGTTTATGCAGGGGTTC RCTCTTTGTGCTGTACAGCTCTATGGATTTTGACAAATGCATGACATCATCTATGCAACATTACAATATCATACAGAATAGTTTCACTGCCCCCAAAATTC Celera SNP ID: hCV29992177 Public SNP ID: rs9471080SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 154684SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (A,94|G,24) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 60):ATGGCAGTAGGTCTACTGGCTGTCAGAGTGAGGGACTGAAGGGGTGTGCACTCCAACCAACTTGAAAGCCACTGTCTTGAGTATCTACGACTAATTAAAC RGTAAAAGGAATTAATCCTGCTGGATCATATGGCTTATCAAGAGACATGAGAGCCACAGGAATAGGTTAAACAGAAAGGTAGGGAGCCTTTTCTGGGAACT Celera SNP ID: hCV2946524 Public SNP ID: rs20456SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 149849Related Interrogated SNP: hCV30225864 (Power = .51) SNP Source: AppleraPopulation (Allele, Count): caucasian (A,23|G,15) african american(A,11|G,27) total (A,34|G,42) SNP Type: INTRON SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (A,67|G,53) SNP Type: INTRON Context (SEQ ID NO: 61):AGGGTCTGGCTCACTCAAAAAGTGCTCTAGGTGTTGCCTTTAGTGAGTCCTCCTCCCTTAGAAATAGTATATCAATATGCAAATCTGTATTACCTTCTGC YTCTGGCTGTTTGAATAAGGGTAGGCTTTGAGCACCCTCCCCAAACCAACCATATGAGGGCATTGTAGATGTCACCTATAATTCACACCTGTAGTTCATTA Celera SNP ID: hCV814553 Public SNP ID: rs302573SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 163798Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (C,13|T,107) SNP Type: INTRON Context (SEQ ID NO: 62):ACATTGGTTTTGTTATACGTTTTGCTTAAAGCCATAGTTTCCAAGAACATATCAATGACTTTGAGGACTTAATGAATACTACTACTAATAATATAACAAT YATTTGTTGAAAATTTACCATGTGACAGATAATATACATAATCTCAGTTAATATTTACAACAACCCTATGAACTTTTCAGAATTCTTTTCAGAACCAACTC Celera SNP ID: hCV814557 Public SNP ID: rs302575SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 165411Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,105)SNP Type: INTRON Context (SEQ ID NO: 63):TTCATTAGAGAAGAGTATACTGTACTTAATATAAAAAAGCCTCACTTTTAAAAGTCATATAGCAATGCACCTGCTAGTTAGGATAGAAATGAAGTAGCCT YTCAGCATCAAAAATATAACTATCATAAACAACTCTCACCTATCAATTCCCTCAGGGAAGAATGGATTCACTTAGGTGGTAATGAAAGGGCATGACTCAGT Celera SNP ID: hCV814585 Public SNP ID: rs160023SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 185932Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: INTRON Context (SEQ ID NO: 64):TTGGCTTGCTACTTAAATGTTACATTATTCTTGTGGCTTCCTTGGAAATCCAGATTTTCATGTACTGATAGAAATACTTCCTCTACCAGATACATAAACA YAGCATAGCAGCTTTCAGCACAATTTCTCTCATTAAAGAAGCAATTCCATTTTTTAAAAAGAATCATACAAAAGAAGTTTGTTATTTTATTTAAAAAGGAT Celera SNP ID: hCV814588 Public SNP ID: rs159958SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 191237Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRONContext (SEQ ID NO: 65):CCAGTCAATTATAAAGTCAAATAACTATAGTAAAAATCTTGCCAGTTGTAATCAATCACTACACATTTGTATAGGAAGGATTTTCCAGAACACCTTGCTT YCTACTTGTGTTCTTTCTATATCTCTCTTTTGGAGGCTATCAAGGTGAGAAATAATAACTAGAAATATCTTTGGTTTATTTGTAAGTGTATCCTCAAGTCC Celera SNP ID: hCV814594 Public SNP ID: rs302596SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 196892Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: INTRON Context (SEQ ID NO: 66):CTGTACGTGAAAATCACATGCCCCAGTATATGTGATTGCTCAGTAAGTACATAGTGCATGCTCAATGAGTATTAGCTATCATCCATTTTTGGCTCCCCAC YGACATTTTTATAGAAAAGGATTTTCATCCCAATTCAGAATTTTACCAAGTTATGAATGTTTTTCTGTATGATTTTTTTCCCCCTTAACTCTTTTTAGATT Celera SNP ID: hDV71111070 Public SNP ID: rs302595SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 197163Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 67):AAGAATAGACTTTTTCATTTCCTAGAAATGAAAAATAATAGCAAAAATTAAAAAATTTAGAGGGATAAAGAAGAATTCACCACTGAAAAGCAAATTACCA YGCTGGAAGTCTGTGCTGACAAATTCTTGCAGAACTCAGAACCACAGGGCAAAGAGAGGAGAACTATGAATGGGAAGTTGTAATATTTGAAGGATAGGACT Celera SNP ID: hCV814600 Public SNP ID: rs302588SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 203632Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 68):TGTTTTGTTTTGTTTTGAGACTCAGAATCTAAATCTAAAACAAATGGTTATAGGAACAGAAGGTATTAATGCCATCATCATTACATGTCCTGCAGCCTAA RTATATAATTGATACACTTAAGCACACTACCACAGTTATCTGAGAATTGAAGGCAACATGAAAAACCACGAGCCCACTGAACAAAATATGGGAAATCCTAC Celera SNP ID: hCV814607 Public SNP ID: rs303701SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 207580Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (G,13|A,107)SNP Type: HUMAN-MOUSE SYNTENIC REGION; INTRON Context (SEQ ID NO: 69):GTTGAATATTTTATTAATTTTTAATTTTGAATATTAAAACCATTATTTTCAATTCAGAGATTTAAAAATAAGCCAATGGTGCTTTTACAACAATTGCACT YTGTTTGTATCTATATAAAGAATACTTTGGGGCCAGGTGCAGTGGTTCACACCTGTAATCCTAGCACTTTGGGAGGCCGAGGCGGGCAGATCACTCGAGGT Celera SNP ID: hCV814610 Public SNP ID: rs159957SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 210926Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): Caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 70):CTTGTTTAGTGTAATATTGGCTTTCTATCCTTATTCATAAAAATATTATTTGAGATAGTGAAGTTTTTTTTTTAAGAAGACAGAACAAGTGCAAGGATGA WTATGAAAATGTTTTGAAATGTATAAAGCACTGTACAAATGGAAAGCATTACCACTGTTAAAACTATCAAAGATTCATTTTATATATCCTTTTTATTAATC Celera SNP ID: hCV814619 Public SNP ID: rs303693SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 215471Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,12|A,104) SNP Type: INTRON Context (SEQ ID NO: 71):TAAAGCACCTGTCAGGTGGCCATTTCTCAAGATACATAAGAATGACTATGCTCCCTTCTAGGCAGAAGAGAGGATGTTTTGAAATATTTAAGAAGCATAA RAAGTGCTGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGGGAGGCCGAGGCGGGCGGATCACAAGATCAGGAGGAGATCGAGACCATCCTAGCTA Celera SNP ID: hCV814621 Public SNP ID: rs303653SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 217178Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HGBASE Population (Allele, Count): caucasian (A,13|G,107)SNP Type: INTRON Context (SEQ ID NO: 72):TACGCATATGCCCCTGGGAGGTTGGTACTATGAGAATATCCTCCAGGAGCCACTTTGTTTTAGCTCGTCTGACTGAGGCCTTAAACAAGGAAAGGAAGAG MGCTGTTAAGGGCACCACAGTAGCACAAATCCAGAGATATTAAGACTTTCCTAACTCAAGTCACAAGGTCTTCCAGCTCAATAACTAATGCTTGATGCATA Celera SNP ID: hCV1416399 Public SNP ID: rs11752840SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 186181Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (A,107|C,13)SNP Type: INTRON Context (SEQ ID NO: 73):TAGTTGTGTTGTCAATGTCCCTTCGGAGGTTTTGAAGTTATAGCTTGCTAAGTTCAGATACATAAAATGCTCACACAATCTTGTCAATGAAGCTTTCCTT MAACAGCAGAAATCCTCTACCTTTTTTTTCTGGGTCATCCAAAACAGTCTTTCAAAAGCTAAATTTTTTTTTGAGCTAAGGAGCCCCAATATTCAATTTAT Celera SNP ID: hCV1703050 Public SNP ID: rs2499450SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 153546Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (C,107|A,13) SNP Type: INTRON Context (SEQ ID NO: 74):GAACATGTCACTGTTCCTAGAATTTTACTGAAATGTATCGGATCATGTGGGTTTTGTTTGCTTCTTTTTTAAAAATATTCTTAGGATCATCAATCTATAC RGAATGAAAATCCTGAGATAGTAACTACATTGGCACCCTTCTCTATTAAACTAATATTGATGCCATATTTTCTATTTTTACTAAGGCTTTTAAGTCAAATC Celera SNP ID: hCV2487638 Public SNP ID: rs11758101SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 75076Related Interrogated SNP: hCV32202303 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (A,99|G,9)SNP Type: INTRON Context (SEQ ID NO: 75):AGTCTCTAGACCATCAAGAAGTCGGCTTCCTGTTTTTAGGTATGACGAGAGATCCATGTGTTTATCCCAGTGCTATAATTCTCTAGATTTGATACAATAG RGGGAACCTGCAGCACACTCAGTCTGACATACTGAAACCACCATATTCAAAATCTTACCCTTAAACTAAGCCTCCTGAAAAACATACAGGATACACAGGAA Celera SNP ID: hCV2487644 Public SNP ID: rs11754132SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 69018Related Interrogated SNP: hCV32202303 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (A,102|G,8)SNP Type: INTRON Context (SEQ ID NO: 76):CCCACTATAGCTGTCCAGAAAGCCTAAAATCTCTCCTTCTAAAATCTACTTAGAGATTCTGGATAAAATATAATACATACTCCTTTTAATGCATAAATTT RCAAAAATGTAAGGAAAATATCTAAGGACCCAAAACAAAGAAGTAAATGAAAATCGAAATAAAAGCTTATGAGCTAATCCTGGGGCACACATAGGAGTGTG Celera SNP ID: hCV3078072 Public SNP ID: rs303675SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 168081Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (G,13|A,107) SNP Type: INTRON; INTERGENIC; UNKNOWN; REPEATSContext (SEQ ID NO: 77):AATGTGTTATATGGTCTCCCCCAATTATATCTTTAGAGAAAATGTTCAGCTTTCTGAAAATAATCTGTTAAGCACCTAACTTAGTCTAAATAGTTTCAGA YTTCTCTTAACTTGTAACGTTCCTGTGAATGTTAACTATAGTGCTTTAAATCAAGAGTGGGTCCCTTCTGAGCATGGGGCCCTGTGTTATGACATAGGTCT Celera SNP ID: hCV3078083 Public SNP ID: rs302593SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 197833Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (T,13|C,107) SNP Type: INTRON Context (SEQ ID NO: 78):GTGCGTGGCCTGGGGCTTTGGGGACCCCTGCTACATAGTCATGCACATAATATCACTGGTTTGGACGAAGTAGAAAAGATGTCTAAATTGGTGAGATTCC WGAATTACAGAATTTTGGACAGAAATGTGATTAGTTTTATTTAGCCTTAATTGCATACAGTAACCAGAATTAAGTTACCATGTGTTAACCCAGTAGAATAA Celera SNP ID: hCV3078087 Public SNP ID: rs11754307SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 202631Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (T,107|A,13)SNP Type: INTRON Context (SEQ ID NO: 79):TGGGAAAGATTCATGAACCTGCAATATATTTTTGTGTTAGTGTTGACCTAGACAAAATGGGCTAAAAGCAATGGACGTTTTGTCCATTACTGAGATATTT MAAAAGCTCTTTCTAGTAGCTTGAAAACCGTATCTTTTCTTTGTAGTTTTATCTAACATCATATCTTTTCACTGACAATGAAGAATATAGCTGATCACATG Celera SNP ID: hCV8948950 Public SNP ID: rs964116SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 111237Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (C,107|A,13) SNP Type: INTRON Context (SEQ ID NO: 80):AAAAAATAATAACATAACAAGACACTATGAAACACAAAAACAGATAGGAAAAAAAAATGACCAAGTAGAACTTCTAAAAATGAAGATATCACCATTGAAA YTTTAAAAACTCAATATAAGGGTTAAATGGAAGATTAGACATAGGTGAGAAAAGGCTTAATGAACTAGAAGAAATATTTGAAGAAACTACTCAAAATGCAA Celera SNP ID: hCV8948982 Public SNP ID: rs303678SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 168820Related Interrogated SNP: hCV32202303 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (C,11|T,105) SNP Type: INTRON; INTERGENIC; UNKNOWN; REPEATSContext (SEQ ID NO: 81):TTAGTCAGGTATGAGTGGACATTAATAGTTCACTGCCAATACCTCACCTGTGGAGTTAATTTTCCTGGCCCAAGAGGGCAAATCAGAGATGTTTAGCTAT YAGATAGAGAGAAATGAGAGAAATGTTTGTGGTGGGTCATTGCTGAAATGCAATGACATAGGCATCAATGTAATGAGGCTAAAAGTAAAGGTGCCTGGTCC Celera SNP ID: hCV16029234 Public SNP ID: rs2499452SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 128596Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,107|C,13)SNP Type: INTRON Context (SEQ ID NO: 82):TCTAGAAAGGGGTTAACCTCATTTCCTCAGACATAAAAACTGTCCTTGGCAGTTGGAAACAGCAGAGTTGACTCCACGGATGACTGATGCCCCTTACGGG KGTTATATACCTGTCCACGCCTGCCCCTGGCAGGGATTTAAACATTCCATGCTGTTCCATGAATCCTAAATCAAATAGATTCATCCTGGCCCTTGGTGAAG Celera SNP ID: hCV27505675 Public SNP ID: rs3818308SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 167246Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,84|G,36) SNP Type: INTRON Context (SEQ ID NO: 83):GACAGAGAGCCTGAGGGGTGAGGCTGCTCAGGGAACAGGTGAGCAGGCAGCTGCAGCCCTCCAGGTTCGGCCACAGGAACCTGGTACTGGGTGACGAGTG KTAGCTTGGTTGGCTTGATATTGCTGTGGAAGAAAGGGTAATTCTTGGTGATACATTGAATGGCCAGCTAGTGCGGAGGAAGAGATTGGAAATAATTCACG Celera SNP ID: hCV29161258 Public SNP ID: rs6901022SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 168697Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,81|G,39)SNP Type: INTRON Context (SEQ ID NO: 84):TGGCAGGAGGCGTGCTTCCTCGGTGCTACCCCCTGGGTTGTGTGGTTGGAAAGAGACAATAACATGGTTGTGGGGAAGTAGAGTCCCTGCTGGTCATCCC RTCATGTAGGGAGACTGGCTCTGGGCCATCCTCATGTGGTGTTTTTGGAGGCTACCTGGATCCTGGCTAGGACGAAGAGCTCCCCTGTGTCTCAGTAGGCG Celera SNP ID: hCV29161261 Public SNP ID: rs6924090SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 150191Related Interrogated SNP: hCV30225864 (Power = .6)Related Interrogated SNP: hCV3054799 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,76|G,42)SNP Type: INTRON Context (SEQ ID NO: 85):CAGGTGATCAGCCTTCTGAAGTGCTGGGATTACAGGCATGAGCCACCGTGCCCAGCCTGATTCTATTTGTACAAAAACATATGGATATATATGCATAGAA RTCAAGGTAAAAGAATATAATCAAACATGTTAATATCAATTACATTTAAGTAGAGGAATTATGGTGATTTTTACTTTCTTCTTTGTGTTTTTCTGCCTAGT Celera SNP ID: hCV29576755 Public SNP ID: rs6899653SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 147064Related Interrogated SNP: hCV30225864 (Power = .7)Related Interrogated SNP: hCV29992177 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,83|G,37)SNP Type: INTRON; REPEATS Context (SEQ ID NO: 86):ACACAGGATGTTGTGTACCTTGTCATGTACTTATTTGCCATCTGTATCTCTTCTTTGGTGAAGTGGCTGTTCAGATCTTTTGCCCACTTTTAAACTGAGT KGTTTATTTTCTTATTGTTGAATTTTTAGAGCTCTTTGTATACTTCAGATACAAGTCCTTTATCAGATATATGTTTTGCAAATATTTTCTCCCAGTCTGTA Celera SNP ID: hCV30280062 Public SNP ID: rs7772430SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 153576Related Interrogated SNP: hCV30225864 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,65|T,51)SNP Type: INTRON; REPEATS Context (SEQ ID NO: 87):TGGCCATGGCTGAAACTCACTGCTTTTGTCTCTCTAGTACAAGGACTGGCAGGGCAAGAGCTGGGGGCCCGTGGGCACGTGGCTGCTGATGAGATCTGGG STCTGATGTTTCTGCTGCACTGTTGAAATGCAGCCTGGGCCAGGATTGTGAACGCTGCCGGTGGTAGGGAGCATGGAGTCTGAGCCATCTCCCACCCAGGA Celera SNP ID: hCV30478066 Public SNP ID: rs9462533SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 168181Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,76|G,44)SNP Type: INTRON Context (SEQ ID NO: 88):AGAGCAATGATTGAGGAAGCTGAATCCTCCTCGTTGTGTTTTTCAGATGTGCTGTGTGGAGTCCTGGAGTTTCAGCGAGAGGGCTCCGTGTGTGGAAGGT SCAGGTATACAGGGGTTGGAATTCAAATTTACTGGCCTCTAGAGGTTGGCAGGTGCCCAGGTGAATGCATGGAGTGGGCCAGGTGCAGGGCACAAATGCTA Celera SNP ID: hCV29703356 Public SNP ID: rs9471079SNP in Genomic Sequence: SEQ ID NO: 5 SNP Position Genomic: 155051Related Interrogated SNP: hCV29992177 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,94|C,24)SNP Type: INTRON Gene Number: 3 Celera Gene: hCG1999777-84000313730953Gene Symbol: KIF6 Protein Name: kinesin family member 6Celera Genomic Axis: GA_x5YUV32W6W6 (12301147..12331055) Chromosome: 6OMIM NUMBER: OMIM Information: Genomic Sequence (SEQ ID NO: 6):SNP Information Context (SEQ ID NO: 89):GCTCCACTGATCCCAGGTGGATTGCTGGAAAGTCTTTTCAAAACATTGCATCAATTTCTCCCATTTGCAGAGGCCAGTGAACTCTGGGAAGGTGCACTGC YGTCAAGCATGTGTCCATATCAAAGGCTGGGCTTCCATTAGGGGATGTTCGGAGCAAAAGGCCCCTTGGCCAGTTGCTGCACACACTTTGCATATGCTCTG Celera SNP ID: hCV792699 Public SNP ID: rs728218SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 18230SNP Source: dbSNP; Celera Population (Allele, Count):caucasian (C,55|T,65) SNP Type: INTRON Context (SEQ ID NO: 90):TTTCAACATCCAACATTCACAGCCAACCTCTCTACACCTGCTCTGCCTCGGAGCCCTGGCAGTCCCTGGACACGTGTTATGGAAGGAACACTGTCTCCCC SACATGCTCACATGGCCCAAATCCCCACAAGTCCCCTTTTTGCCAAGCTCCACGTCCTTTGCCTCTTCCCATCACCCAATACCCAACCTGCCATCATTGTC Celera SNP ID: hCV1650850 Public SNP ID: rs35268572SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 15182SNP Source: Celera Population (Allele, Count): no pop (C,-|G,-)SNP Type: INTRON Context (SEQ ID NO: 91):GGAGGAATGATGGTTGGTTTCTATGGATTTGTTACAGGGGAAGGGATATCTCAGCTCAAAGGATATCCTGCGTATCCAAGCCTTCCTCCACTTGTGCCCC RCACACTGTCCCCTCTACTTTCTCAAGGAAGTTTTTCCTGCAGCTCTGCTCCCCTCTCCCACCACAGCATCAGTTTCCCTCTCTATGCATGTTTCAGCACG Celera SNP ID: hCV3054813 Public SNP ID: rs9471077SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 25198SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (A,73|G,47) SNP Type: INTRON; REPEATS Context (SEQ ID NO: 92):TCAGAAACTGCATCTTTCTTTTTTTTAAGGAGCAGGATTCCTCTTGCACATGAAATCTTTCCCAGAGCCCCAATCTGAAGCCTACTTAAGAGTGGAGCTC WGGTTGAAGTAGGGGCAGAGGGCTCCCATTTCCACCAGCCCAGAGAGTGTGATTTCAAGAGCCCTTACCCGTAATTCTGAAATGGATGCCCTTGTCTAAGT Celera SNP ID: hCV3054822 Public SNP ID: rs11751357SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 12718SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):caucasian (T,90|A,28) SNP Type: INTRON Context (SEQ ID NO: 93):AGACTGTGTGCTGTAGGAACTGGGGAGCAGCCAGGGTTCTGGAGCCTCCTAGCTTTCCACCAGCAGCGTGGCCTGACCACTCTCTACTCGCCCCAGGTGC YTCCCATCCGCCGTTTCTCTGCCTTGGGGCTCCACTCCTGGCTGACCTCCTGGCATCTGGTCAGATCCATGCCCATTGCCCTCTGCTGCTTTATCTTGGTA Celera SNP ID: hCV3054829 Public SNP ID: rs4535541SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 9422SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (C,52|T,44) SNP Type: INTERGENIC; UNKNOWNContext (SEQ ID NO: 94):GTAGAGGCTGCGGTCACTCCCCTCGTCAATGCTGGTTCCTGTTCCTGAGGCCGAGAGAACTCCTGACAGCAGAGTGGGCATATCTTGGTAGTTGCAGCTT YTCAAGACAGTGTGGCCCAGTGGGGAGAGAGCAGAAAACCTGGGTTATGCTGGCTCTGCCATTTATCAGCTGTGTAACCTTGGGCAAGTGATACAACCTCT Celera SNP ID: hCV15876373 Public SNP ID: rs2281686SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 24663SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):caucasian (T,105|C,15) SNP Type: INTRON Context (SEQ ID NO: 95):AGCAGGCTGGCGGCCAAGCAAGGCGAGTACAGGACCAAGGCCGGCTCTCAGTTGCGGCGCTCCATCCATGCACAAACCTCTTCCTGCCCAAACTGCACAC RGCTGGTGGAGAAGCTGAGTGCAGGCGCCACAGGGCAGGCATCAGTCATTATACATCGAATCTGCCAGCCCATACCATCACGGTGGGGGCGCCTTTCTGGC Celera SNP ID: hCV30478067 Public SNP ID: rs9471078SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 27091SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (G,108|A,12) SNP Type: INTRON Context (SEQ ID NO: 96):CTGGGCTTCCATTAGGGGATGTTCGGAGCAAAAGGCCCCTTGGCCAGTTGCTGCACACACTTTGCATATGCTCTGGACACCAGTGGCCCCAGATCCCATG YTGTGTGTTTTTCTGTCTTCATTTCCTTTCCTGTCTTAGTGATTGCCCCAGGAGGCTGGTTCACACCCCGCATGGGGCCATGCCACACATCTCTGTCAGTA Celera SNP ID: hCV792698 Public SNP ID: rs728217SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 18356Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,63|C,55) SNP Type: INTRON Context (SEQ ID NO: 97):TCCTTTCCCTCCTCCCCAGCTAGCAGAACCCCGGCTTTGTAAGTGTTAACCCCAGGTAATTGAGCATAATTGGTCTAAGTCATAGTGCTAATCTTGCTCC MCTCTGTCTCAGCCCCTGAGAGCAGTGAAGTCACTGAAGACCCATAAGACAGTGGGCAAGAGGGCCAGGCTGAGGAGAAAGCCAAACAAGGCACCACAGTC Celera SNP ID: hCV8948890 Public SNP ID: rs1328384SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 8245Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (C,73|A,45)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 98):TCAGTCAGAGCCTGGGGGAAGTCAGAGTGACACCAGCCTGAGAAACACATCTGGGTTCTGGCTCGTCTACTCATGAACTGAAGGACCGTTTACTGAACAG YGACTCTGTGCTTGGGACACAGCAATGAGCAAGACAAACAGGTCCCTGTTGCATTGGAGCTCTTAGTATTATGGGGGGTTGCAGGTATTTCAAAAATAGGC Celera SNP ID: hCV11606396 Public SNP ID: rs1887716SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 19270Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (C,69|T,51)SNP Type: INTRON Context (SEQ ID NO: 99):GCTGTTTCCTTTAATGAGCTGTGGCTGCAGACACTGTGAGTTGCCTGCTGAGTATCCTTTCCCTCCTCCCCAGCTAGCAGAACCCCGGCTTTGTAAGTGT YAACCCCAGGTAATTGAGCATAATTGGTCTAAGTCATAGTGCTAATCTTGCTCCCCTCTGTCTCAGCCCCTGAGAGCAGTGAAGTCACTGAAGACCCATAA Celera SNP ID: hCV26547610 Public SNP ID: rs5006081SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 8191Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:Celera; HapMap Population (Allele, Count): caucasian (T,73|C,43)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 100):GATTGGCCTTCAGGATGCCCTGCATTCCACTGCCTTGCCTGTGGCTGGGACATCCTGCCTGGACCTGTCATGGCCATTTCTGGGCTTCCAAACCAGAGCA YGGGCCAAGGGAGAGAGCTGGCAAATCGTTAAAAATAAAAATATTCCCCCCACATTCCACTGGTGTGAGCATCCTCTGACATTATATTTTGATGGTGCTAT Celera SNP ID: hCV27495641 Public SNP ID: rs3823213SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 20308Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,89|T,31)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 101):TCTAGAAAGGGGTTAACCTCATTTCCTCAGACATAAAAACTGTCCTTGGCAGTTGGAAACAGCAGAGTTGACTCCACGGATGACTGATGCCCCTTACGGG KGTTATATACCTGTCCACGCCTGCCCCTGGCAGGGATTTAAACATTCCATGCTGTTCCATGAATCCTAAATCAAATAGATTCATCCTGGCCCTTGGTGAAG Celera SNP ID: hCV27505675 Public SNP ID: rs3818308SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 23970Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,84|G,36) SNP Type: INTRON Context (SEQ ID NO: 102):ATGTCCTTAGACCCTGCAGGGCAGATGGCTCCCTGGAGACACAGCTGTTCAGGCACTGCCTCCAGGTCATCCTGGCCAAGAGGCTGATGGTGAAAGATGT RGTCTGGGAGATCAGGATTGGCCTTCAGGATGCCCTGCATTCCACTGCCTTGCCTGTGGCTGGGACATCCTGCCTGGACCTGTCATGGCCATTTCTGGGCT Celera SNP ID: hCV29161257 Public SNP ID: rs6904582SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 20193Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,69|A,51)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 103):GACAGAGAGCCTGAGGGGTGAGGCTGCTCAGGGAACAGGTGAGCAGGCAGCTGCAGCCCTCCAGGTTCGGCCACAGGAACCTGGTACTGGGTGACGAGTG KTAGCTTGGTTGGCTTGATATTGCTGTGGAAGAAAGGGTAATTCTTGGTGATACATTGAATGGCCAGCTAGTGCGGAGGAAGAGATTGGAAATAATTCACG Celera SNP ID: hCV29161258 Public SNP ID: rs6901022SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 22519Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,81|G,39)SNP Type: INTRON Context (SEQ ID NO: 104):AATTTGGTCTTCCTCTGGTTCTACAGACTTTACAGAGGGCTTACTATGTTCCATTGAACTGTGAGGGCCAGGAGTGGACCAGAGATGCTGGCCCCTGTCC YGATGGGATTCAGTCAGAGCCTGGGGGAAGTCAGAGTGACACCAGCCTGAGAAACACATCTGGGTTCTGGCTCGTCTACTCATGAACTGAAGGACCGTTTA Celera SNP ID: hCV30532403 Public SNP ID: rs7754225SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 19161Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,65|T,55)SNP Type: INTRON Context (SEQ ID NO: 105):TGAGGTATGGTCGCACCACTGCACCCCAGCCTGGCTGACAGAGACCCCCCCCATCTCAAAAAATAAATAAAAGAAAGTAAAAATAAAAGAAAATAAAAGT YAGTAGACTCTACCCAGCTCTAGAGGGCTGAGGGCACTAAGGCATGCCAAGAATACTGCTGCTGCTACATAGGGGACTGGGGCAAATGCCATGCCATCTTC Celera SNP ID: hCV30190183 Public SNP ID: rs7774046SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 18870Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source: dbSNP Population (Allele, Count): caucasian (T,65|C,55) SNP Type: INTRONContext (SEQ ID NO: 106):AAAGAAAGTAAAAATAAAAGAAAATAAAAGTTAGTAGACTCTACCCAGCTCTAGAGGGCTGAGGGCACTAAGGCATGCCAAGAATACTGCTGCTGCTACA YAGGGGACTGGGGCAAATGCCATGCCATCTTCAGGGCTCTTGAGAGTGTGTGTGTGTATGTGTGTGTGTGTGTGCAGTTACATGTGTGTTCCATGGACTCT Celera SNP ID: hCV30082078 Public SNP ID: rs7774204SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 18939Related Interrogated SNP: hCV3054822 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,65|C,55)SNP Type: INTRON Context (SEQ ID NO: 107):TGGCTGTTGGAAACATGAACTCTTCCCAACACAGTGTTATCTCAGGAAATTATTCCACCTGCTTCCTCCTGGTGGTTCTTTCCCCTGCCTTGGGTAATTT STTCACATGCAGATGTTGATCGGTAGTTAGCTGAAGACTCAAGGGTAACCCTCTGAAGATCTCCAGAGCATGCTCTCTCTCTTTCTCTCTCTTTTTTCTCC Celera SNP ID: hCV30586596 Public SNP ID: rs9369112SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 16913Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,88|G,32)SNP Type: INTRON Context (SEQ ID NO: 108):CAAATGCCATGCCATCTTCAGGGCTCTTGAGAGTGTGTGTGTGTATGTGTGTGTGTGTGTGCAGTTACATGTGTGTTCCATGGACTCTTGGGGAGGCTTC YAGAATCAGAATTTGGTCTTCCTCTGGTTCTACAGACTTTACAGAGGGCTTACTATGTTCCATTGAACTGTGAGGGCCAGGAGTGGACCAGAGATGCTGGC Celera SNP ID: hCV29902034 Public SNP ID: rs9380848SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 19052Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,89|C,31)SNP Type: INTRON Context (SEQ ID NO: 109):CCCCCAGGCAGCTATGTTTTTCCCTGTGGAAGTGGGGAGTGTCAGCCCAAATCCTCCCAAGTGGCTGGGTGAAGGTTGTGAGGCCCAAGGTACCCACACT RCCCTCTCTCAAGCTCTCAGCAGAGCCCCTGGGAGCTGCCCACTGTTCTCTGGGTGCTATGATGTCCTTAGACCCTGCAGGGCAGATGGCTCCCTGGAGAC Celera SNP ID: hCV29937959 Public SNP ID: rs9462531SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 20032Related Interrogated SNP: hCV3054822 (Power = .8) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,77|A,41)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 110):TGGCCATGGCTGAAACTCACTGCTTTTGTCTCTCTAGTACAAGGACTGGCAGGGCAAGAGCTGGGGGCCCGTGGGCACGTGGCTGCTGATGAGATCTGGG STCTGATGTTTCTGCTGCACTGTTGAAATGCAGCCTGGGCCAGGATTGTGAACGCTGCCGGTGGTAGGGAGCATGGAGTCTGAGCCATCTCCCACCCAGGA Celera SNP ID: hCV30478066 Public SNP ID: rs9462533SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic: 23035Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (C,76|G,44)SNP Type: INTRON Context (SEQ ID NO: 111):TCAGTTTTTCACAAACCACCCAAGCCCAATAAGACTTCACCTGGCTGGGGTTTAGGATAGAGTCTTTCTCAGAAGCATGTTCAGTTTAATGGGGGACTTC YGAAAACCCTAGGGCCACAAAAGCCACAGAAAGGGCAACATAATGGTGGACTTTGGGGGAGATCTCAGCTCAAGAGGCCCACAGACTGTGCTGTAGGAACT Celera SNP ID: hDV70715992 Public SNP ID:rs16891930 SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic:10967 Related Interrogated SNP: hCV3054822 (Power = .9) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,95|C,23)SNP Type: INTRON Context (SEQ ID NO: 112):GGACCCCGTGTCAACCTGTCTTTGGCTTCCTTTGTGGCCCCGTGGTCACTGAAAAGCCAGAATGAATATTCTTCCTTTCGGAATAAAAATTGAGCTGTGG RAGTTTTGTTTGCTTTGATGAATTACTTCCAGGCTGCTGTTTATTTGGAGAGCAAAGCTCCCCAGCTGCAGGGTGGGTAGAGGCTGCGGTCACTCCCCTCG Celera SNP ID: hDV70716012 Public SNP ID:rs16891961 SNP in Genomic Sequence: SEQ ID NO: 6 SNP Position Genomic:24487 Related Interrogated SNP: hCV3054822 (Power = .6) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (A,83|G,35)SNP Type: INTRON Gene Number: 4 Celera Gene: hCG2041191-209000073583183Gene Symbol: KIF6 Protein Name: kinesin family member 6Celera Genomic Axis: GA_x5YUV32W6W6 (12667048..12720760) Chromosome: 6OMIM NUMBER: OMIM Information: Genomic Sequence (SEQ ID NO: 7):SNP Information Context (SEQ ID NO: 113):TTCATTAGAGAAGAGTATACTGTACTTAATATAAAAAAGCCTCACTTTTAAAAGTCATATAGCAATGCACCTGCTAGTTAGGATAGAAATGAAGTAGCCT YTCAGCATCAAAAATATAACTATCATAAACAACTCTCACCTATCAATTCCCTCAGGGAAGAATGGATTCACTTAGGTGGTAATGAAAGGGCATGACTCAGT Celera SNP ID: hCV814585 Public SNP ID: rs160023SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 11247Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: INTRON Context (SEQ ID NO: 114):TTGGCTTGCTACTTAAATGTTACATTATTCTTGTGGCTTCCTTGGAAATCCAGATTTTCATGTACTGATAGAAATACTTCCTCTACCAGATACATAAACA YAGCATAGCAGCTTTCAGCACAATTTCTCTCATTAAAGAAGCAATTCCATTTTTTAAAAAGAATCATACAAAAGAAGTTTGTTATTTTATTTAAAAAGGAT Celera SNP ID: hCV814588 Public SNP ID: rs159958SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 16552Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRONContext (SEQ ID NO: 115):CCAGTCAATTATAAAGTCAAATAACTATAGTAAAAATCTTGCCAGTTGTAATCAATCACTACACATTTGTATAGGAAGGATTTTCCAGAACACCTTGCTT YCTACTTGTGTTCTTTCTATATCTCTCTTTTGGAGGCTATCAAGGTGAGAAATAATAACTAGAAATATCTTTGGTTTATTTGTAAGTGTATCCTCAAGTCC Celera SNP ID: hCV814594 Public SNP ID: rs302596SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 22207Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (C,13|T,107)SNP Type: INTRON Context (SEQ ID NO: 116):CTGTACGTGAAAATCACATGCCCCAGTATATGTGATTGCTCAGTAAGTACATAGTGCATGCTCAATGAGTATTAGCTATCATCCATTTTTGGCTCCCCAC YGACATTTTTATAGAAAAGGATTTTCATCCCAATTCAGAATTTTACCAAGTTATGAATGTTTTTCTGTATGATTTTTTTCCCCCTTAACTCTTTTTAGATT Celera SNP ID: hDV71111070 Public SNP ID: rs302595SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 22478Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 117):AAGAATAGACTTTTTCATTTCCTAGAAATGAAAAATAATAGCAAAAATTAAAAAATTTAGAGGGATAAAGAAGAATTCACCACTGAAAAGCAAATTACCA YGCTGGAAGTCTGTGCTGACAAATTCTTGCAGAACTCAGAACCACAGGGCAAAGAGAGGAGAACTATGAATGGGAAGTTGTAATATTTGAAGGATAGGACT Celera SNP ID: hCV814600 Public SNP ID: rs302588SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 28947Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): Caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 118):TGTTTTGTTTTGTTTTGAGACTCAGAATCTAAATCTAAAACAAATGGTTATAGGAACAGAAGGTATTAATGCCATCATCATTACATGTCCTGCAGCCTAA RTATATAATTGATACACTTAAGCACACTACCACAGTTATCTGAGAATTGAAGGCAACATGAAAAACCACGAGCCCACTGAACAAAATATGGGAAATCCTAC Celera SNP ID: hCV814607 Public SNP ID: rs303701SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 32895Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (G,13|A,107)SNP Type: HUMAN-MOUSE SYNTENIC REGION; INTRON Context (SEQ ID NO: 119):GTTGAATATTTTATTAATTTTTAATTTTGAATATTAAAACCATTATTTTCAATTCAGAGATTTAAAAATAAGCCAATGGTGCTTTTACAACAATTGCACT YTGTTTGTATCTATATAAAGAATACTTTGGGGCCAGGTGCAGTGGTTCACACCTGTAATCCTAGCACTTTGGGAGGCCGAGGCGGGCAGATCACTCGAGGT Celera SNP ID: hCV814610 Public SNP ID: rs159957SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 36241Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 120):CTTGTTTAGTGTAATATTGGCTTTCTATCCTTATTCATAAAAATATTATTTGAGATAGTGAAGTTTTTTTTTTAAGAAGACAGAACAAGTGCAAGGATGA WTATGAAAATGTTTTGAAATGTATAAAGCACTGTACAAATGGAAAGCATTACCACTGTTAAAACTATCAAAGATTCATTTTATATATCCTTTTTATTAATC Celera SNP ID: hCV814619 Public SNP ID: rs303693SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 40786Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,12|A,104) SNP Type: INTRON Context (SEQ ID NO: 121):TAAAGCACCTGTCAGGTGGCCATTTCTCAAGATACATAAGAATGACTATGCTCCCTTCTAGGCAGAAGAGAGGATGTTTTGAAATATTTAAGAAGCATAA RAAGTGCTGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGGGAGGCCGAGGCGGGCGGATCACAAGATCAGGAGGAGATCGAGACCATCCTAGCTA Celera SNP ID: hCV814621 Public SNP ID: rs303653SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 42493Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HGBASE Population (Allele, Count): caucasian (A,13|G,107)SNP Type: INTRON Context (SEQ ID NO: 122):CCTTTGCTGCTTCCTCTCTCTAGCATATCTACATCCAAATAGTTTCCAAGTCCTGGTTATGCTGCCTCCTGAATAATTTTTTCCTCCCTCCCCTCAACTT YGTCCTCACTACTTACTACTTGCTTTAGTTTGGCTCTTAGTCTCTTTGCCAGAACTAGCAAAGTTCTCCTAACTGCTTTTCCTGCCTCTAATCCCGCCCTC Celera SNP ID: hCV814633 Public SNP ID: rs303649SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 50875Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTERGENIC; UNKNOWN; REPEATS Context (SEQ ID NO: 123):TACGCATATGCCCCTGGGAGGTTGGTACTATGAGAATATCCTCCAGGAGCCACTTTGTTTTAGCTCGTCTGACTGAGGCCTTAAACAAGGAAAGGAAGAG MGCTGTTAAGGGCACCACAGTAGCACAAATCCAGAGATATTAAGACTTTCCTAACTCAAGTCACAAGGTCTTCCAGCTCAATAACTAATGCTTGATGCATA Celera SNP ID: hCV1416399 Public SNP ID: rs11752840SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 11496Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (A,107|C,13)SNP Type: INTRON Context (SEQ ID NO: 124):AATGTGTTATATGGTCTCCCCCAATTATATCTTTAGAGAAAATGTTCAGCTTTCTGAAAATAATCTGTTAAGCACCTAACTTAGTCTAAATAGTTTCAGA YTTCTCTTAACTTGTAACGTTCCTGTGAATGTTAACTATAGTGCTTTAAATCAAGAGTGGGTCCCTTCTGAGCATGGGGCCCTGTGTTATGACATAGGTCT Celera SNP ID: hCV3078083 Public SNP ID: rs302593SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 23148Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):caucasian (T,13|C,107) SNP Type: INTRON Context (SEQ ID NO: 125):GTGCGTGGCCTGGGGCTTTGGGGACCCCTGCTACATAGTCATGCACATAATATCACTGGTTTGGACGAAGTAGAAAAGATGTCTAAATTGGTGAGATTCC WGAATTACAGAATTTTGGACAGAAATGTGATTAGTTTTATTTAGCCTTAATTGCATACAGTAACCAGAATTAAGTTACCATGTGTTAACCCAGTAGAATAA Celera SNP ID: hCV3078087 Public SNP ID: rs11754307SNP in Genomic Sequence: SEQ ID NO: 7 SNP Position Genomic: 27946Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (T,107|A,13)SNP Type: INTRON Gene Number: 5 Celera Gene: Chr6:40760720..40800720Gene Symbol: Protein Name: Celera Genomic Axis:GA_x5YUV32W6W6 (12225041..12265041) Chromosome: 6 OMIM NUMBER:OMIM Information: Genomic Sequence (SEQ ID NO: 8): SNP InformationContext (SEQ ID NO: 126):CTAATGTATTTTTTATTCTGTGGAGATGGGTAGCTAGAACCACAGACACGCACCATCATATCCTGCTAATTTTTAAATCTTTTGTGGAGATGAGGTCTCT YGATGCTGCCCAGGAAGTCTCAAACTCCTGGCCTCAAGAGATCCTCTCACCTTAGGCTTTTGAAGTGCTGGGATTATAGGCATGAGCCTCTGCACCTGCCC Celera SNP ID: hCV29649182 Public SNP ID: rs9471032SNP in Genomic Sequence: SEQ ID NO: 8 SNP Position Genomic: 20000SNP Source: dbSNP; HapMap Population (Allele, Count):caucasian (C,104|T,16) SNP Type: INTERGENIC; UNKNOWN; REPEATSGene Number: 6 Celera Gene: Chr6:41237467..41290799 Gene Symbol:Protein Name: Celera Genomic Axis: GA_x5YUV32W6W6 (12701788..12755120)Chromosome: 6 OMIM NUMBER: OMIM Information:Genomic Sequence (SEQ ID NO: 9): SNP InformationContext (SEQ ID NO: 127):GTTGAATATTTTATTAATTTTTAATTTTGAATATTAAAACCATTATTTTCAATTCAGAGATTTAAAAATAAGCCAATGGTGCTTTTACAACAATTGCACT YTGTTTGTATCTATATAAAGAATACTTTGGGGCCAGGTGCAGTGGTTCACACCTGTAATCCTAGCACTTTGGGAGGCCGAGGCGGGCAGATCACTCGAGGT Celera SNP ID: hCV814610 Public SNP ID: rs159957SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic: 1501Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTRON Context (SEQ ID NO: 128):CTTGTTTAGTGTAATATTGGCTTTCTATCCTTATTCATAAAAATATTATTTGAGATAGTGAAGTTTTTTTTTTAAGAAGACAGAACAAGTGCAAGGATGA WTATGAAAATGTTTTGAAATGTATAAAGCACTGTACAAATGGAAAGCATTACCACTGTTAAAACTATCAAAGATTCATTTTATATATCCTTTTTATTAATC Celera SNP ID: hCV814619 Public SNP ID: rs303693SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic: 6046Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):caucasian (T,12|A,104) SNP Type: INTRON Context (SEQ ID NO: 129):TAAAGCACCTGTCAGGTGGCCATTTCTCAAGATACATAAGAATGACTATGCTCCCTTCTAGGCAGAAGAGAGGATGTTTTGAAATATTTAAGAAGCATAA RAAGTGCTGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGGGAGGCCGAGGCGGGCGGATCACAAGATCAGGAGGAGATCGAGACCATCCTAGCTA Celera SNP ID: hCV814621 Public SNP ID: rs303653SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic: 7753Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HGBASE Population (Allele, Count): caucasian (A,13|G,107)SNP Type: INTRON Context (SEQ ID NO: 130):CCTTTGCTGCTTCCTCTCTCTAGCATATCTACATCCAAATAGTTTCCAAGTCCTGGTTATGCTGCCTCCTGAATAATTTTTTCCTCCCTCCCCTCAACTT YGTCCTCACTACTTACTACTTGCTTTAGTTTGGCTCTTAGTCTCTTTGCCAGAACTAGCAAAGTTCTCCTAACTGCTTTTCCTGCCTCTAATCCCGCCCTC Celera SNP ID: hCV814633 Public SNP ID: rs303649SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic: 16135Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count): caucasian (T,13|C,107)SNP Type: INTERGENIC; UNKNOWN; REPEATS Context (SEQ ID NO: 131):GTGCATAATCAAGTACTCTAAGACTTAGTGTCATAAAGCAACCATTTATTTTGTTCATGGATTCTCTGGGTCGGGAATCCAGAAAGGACAGAGGGGTCAA RGCTGGTCTCTGTGTCACAATGTCAGGAGCCTCAGCTGGAAGACTGGAAGCTGGGGATAGGAATACTCATTGGAAGCTCCTTTACTCACATGTCTGGCTAT Celera SNP ID: hCV1416391 Public SNP ID: rs11751730SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic: 33332Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count): caucasian (G,106|A,10)SNP Type: INTERGENIC; UNKNOWN; REPEATS Context (SEQ ID NO: 132):CCACTGGAAATATTTCAGAATTCCAGATGCTCTCTATCCTCATCAGCACTTGGTATTGACACTTAAGAAATTTTTTAGCCATTTAGTAAGTACTAGTGGG RGTGGAGCCAAGATGGCCGAATAGGAACAGCTCCAGTCTACAGCTCCCAGCATAAGCAACACAGAAGACGAATGATTTCTGCATTTCCAACTGAGGTACTG Celera SNP ID: hCV32203040 Public SNP ID:rs11755914 SNP in Genomic Sequence: SEQ ID NO: 9 SNP Position Genomic:20000 Related Interrogated SNP: hCV32202303 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): caucasian (G,106|A,14)SNP Type: INTERGENIC; UNKNOWN; REPEATS

TABLE 3 Primer 1 Primer 2 (Allele-specific (Allele-specific MarkerAlleles Primer) Primer) Common Primer hCV15876373 C/T GGCCACACTGTCTTGAGGCCACACTGTCTTGA AGCTGCAGGGTGGGTA G A GAG (SEQ ID NO: 133)(SEQ ID NO: 134) (SEQ ID NO: 135) hCV1650850 C/G GGCCATGTGAGCATGTGGCCATGTGAGCATGT AACATTCACAGCCAAC G C CTCTCTACA (SEQ ID NO: 136)(SEQ ID NO: 137) (SEQ ID NO: 138) hCV29649182 C/T TTGTGGAGATGAGGTCTTTGTGGAGATGAGGT AGGATTGGGAGAGGGA TCTC CTCTT GGTG (SEQ ID NO: 139)(SEQ ID NO: 140) (SEQ ID NO: 141) hCV29992177 A/G TGAATCGTAGACGGAGCACGAGTTGCCACGGA CTCTTTGTGCTGTACA CTTAGGACGCGTTTAT CTTCATTGTTTTATGC GGCAGGGGTTCA AGGGGTTCG (SEQ ID NO: 144) (SEQ ID NO: 142) (SEQ ID NO: 143)hCV30225864 A/G GCCCAAGCGGAAGGTA CACGGGAGAGATTGTT GAGAGCCAGAGAAGATCGACTTTCCATTTTAA TTGCCAGAGAATTTTA G GGACAAGAAAACT AGGACAAGAAAACC(SEQ ID NO: 147) (SEQ ID NO: 145) (SEQ ID NO: 146) hCV30388472 C/TCCTTCTTTGAAAGTCA CCTTCTTTGAAAGTCA CCTGGGCCCATTTCTG TCAGACAC TCAGACATAAACT (SEQ ID NO: 148) (SEQ ID NO: 149) (SEQ ID NO: 150) hCV30478067 A/GGCCCAAACTGCACACA  GCCCAAACTGCACACG AGGCTTAACATTGCCT (SEQ ID NO: 151)(SEQ ID NO: 152) TCACATTG (SEQ ID NO: 153) hCV3054766 A/CGATGATAAGCCATTCC GATGATAAGCCATTCC CCCCACATTCCTGGAG CAGTT  CAGTGTACTAACAGTTTAT (SEQ ID NO: 154) (SEQ ID NO: 155) (SEQ ID NO: 156)hCV3054789 A/T CCTCACCTTGTTTGAG CCTCACCTTGTTTGAG TGATTGGGAAGCCAGA AAGAAAGT ATCTTTG (SEQ ID NO: 157) (SEQ ID NO: 158) (SEQ ID NO: 159)hCV3054799 A/G CGGGTAGAAGCCGACC CACGGGTTCCGAGCCC GGTCCCAACTCCTCTAAGTGTCTAGACTCCC AGTCTATAGACTCCCA (SEQ ID NO: 162) AGCATGAAT GCATGAAC(SEQ ID NO: 160) (SEQ ID NO: 161) hCV3054805 C/G GAACCCCTGGCTATTTGAACCCCTGGCTATTT ACACACACACACATGC CTG CTC ACATGTAC (SEQ ID NO: 163)(SEQ ID NO: 164) (SEQ ID NO: 165) hCV3054808 A/C GACCAGAGGTAGCCACGACCAGAGGTAGCCAC AAGCCCTTTCTCCTTC A C CCTTCTC (SEQ ID NO: 166)(SEQ ID NO: 167) (SEQ ID NO: 168) hCV3054809 A/G GCAGATTAGCTTCGAGCGAGCGAGGTCAATAG CTACTCAGGATTCTTT AGAGACGCCTGGCAGA GTTCCAGCTTGGCAGA GAGATCGGGAA ATCGGGAG (SEQ ID NO: 171) (SEQ ID NO: 169) (SEQ ID NO: 170)hCV3054813 A/G CGGTGTTGAGCCCATA CGGGTAGAAGCCGACC GGGGCACAAGTGGACCTAGTGGTGAGGGGA AAGTGTCTAAGGGGAC (SEQ ID NO: 174) CAGTGTGT AGTGTGC(SEQ ID NO: 172) (SEQ ID NO: 173) hCV3054822 A/T CTGCCCCTACTTCAACTGCCCCTACTTCAACC GAAACAGACAAACAAA CT A CACACCTGTTAC (SEQ ID NO: 175)(SEQ ID NO: 176) (SEQ ID NO: 177) hCV3054829 C/T ACGGCGGATGGGAGAACGGCGGATGGGAA AGAACACACTCCAGGT (SEQ ID NO: 178) (SEQ ID NO: 179)ATTTCTGGTAATT (SEQ ID NO: 180) hCV31340487 C/T GCTGGATCTTGCAGCTGCTGGATCTTGCAGCT CATACCTCTGGATGGG TC TT GATGTGT (SEQ ID NO: 181)(SEQ ID NO: 182) (SEQ ID NO: 183) hCV32202303 C/G GAAATCTCTTTTCGATGAAATCTCTTTTCGAT ACTGAAGTGGAAAGCT TGAACAGC TGAACAGG GAATTCTAGA(SEQ ID NO: 184) (SEQ ID NO: 185) (SEQ ID NO: 186) hCV792699 C/TATGGACACATGCTTGA GATATGGACACATGCT TCATCCGTGGCTCCAC CG TGACA TGAT(SEQ ID NO: 187) (SEQ ID NO: 188) (SEQ ID NO: 189)

TABLE 5 Association of KIF6 Trp719Arg (hCV3054799) with MI and CHD inthe placebo arms of CARE and WOSCOPS On-trial Unadjusted Adjusted^(†)Study Genotype MI* Total* HR 95% Cl p Value HR 95% Cl p Value CARE GG 16155 1.33 0.75-2.35 0.33 1.33 0.75-2.36 0.33 GA 82 636 1.63 1.13-2.350.009 1.54 1.07-2.23 0.02 GG + GA 98 791 1.57 1.10-2.25 0.013 1.501.05-2.15 0.03 AA 44 542 1.00 ref 1.00 ref Matched^(‡) Adjusted^(†‡)Study Genotype Case* Control* OR 95% Cl p Value OR 95% Cl p ValueWOSCOPS GG 35 59 1.49 0.92-2.40 0.10 1.48 0.91-2.41 0.11 GA 137 204 1.611.18-2.21 0.003 1.56 1.14-2.15 0.006 GG + GA 172 263 1.59 1.18-2.140.003 1.55 1.14-2.09 0.005 AA 104 256 1.00 ref 1.00 ref *Data forpatients presented as number of patients ^(†)Adjusted for age(continuous), sex, smoking (current versus non-current) (except inWOSCOPS, where no adjustments for age and smoking were made becausecases and controls were matched), history of hypertension, history ofdiabetes, BMI (continuous), baseline LDL-C level (continuous), andbaseline HDL-C level (continuous). ^(‡)Cases and controls were matchedfor age (in two-year age groups) and smoking (current versusnon-current), all were men.

TABLE 6 Effect of pravastatin on MI and CHD in KIF6 Trp719Arg(hCV3054799) subgroups: CARE and WOSCOPS On-trial UnadjustedAdjusted^(†) Study Genotype Treatment MI* Total* HR 95% CI p Value HR95% CI p Value CARE GG + GA Pravastatin 64 810 0.63 0.46-0.86 0.004 0.630.46-0.87 0.005 Placebo 98 791 1.00 ref 1.00 ref AA Pravastatin 39 5540.86 0.56-1.33 0.50 0.80 0.52-1.24 0.32 Placebo 44 542 1.00 ref 1.00 refp interaction 0.25^(§) p interaction 0.39^(§) Matched^(‡) Adjusted^(†‡)Study Genotype Treatment Case* Control* OR^(†) 95% CI^(†) p Value OR*95% CI p Value WOSCOPS GG + GA Pravastatin 108 330 0.50 0.38-0.67<0.0001 0.50 0.38-0.67 <0.0001 Placebo 172 263 1.00 ref 1.00 ref AAPravastatin 81 213 0.94 0.67-1.33 0.73 0.91 0.64-1.28 0.58 Placebo 104256 1.00 ref 1.00 ref p interaction 0.006^(§) p interaction 0.011^(§)*Data for patients presented as number of patients ^(†)Adjusted for age(continuous), smoking (current versus non-current) (except in WOSCOPS,where no adjustment for age and smoking were made because cases andcontrols were matched), history of hypertension, history of diabetes,BMI (continuous), baseline LDL-C level (continuous), and baseline HDL-Clevel (continuous). ^(‡)Cases and controls were matched for age (intwo-year age groups) and smoking (current versus non-current), all weremen. ^(§)Likelihood ratio test of interaction between KIF6 hCV3054799genotype and treatment.

TABLE 7 Effect of Atorvastatin vs Pravastatin on CHD according to KIF6Trp719Arg genotype On-trial Unadjusted Model 1† Subgroup Treatment CHD*Total* HR 95% CI P Value HR 95% CI P Value ArgArg + Atorvastatin 76 5090.57 0.43-0.76 0.0001 0.56 0.42-0.75 <0.0001 ArgTrp Pravastatin 123 5021.00 ref 1.00 ref TrpTrp Atorvastatin 81 359 0.99 0.73-1.35 0.96 0.970.70-1.32 0.82 Pravastatin 80 352 1.00 ref 1.00 ref P interaction =0.01§ P interaction = 0.01§ HR denotes hazard ratio, CI: confidenceinterval, ref: reference group; ArgArg + ArgTrp = GG + GA; TrpTrp = AA,respectively *Number of patients. †Model 1: adjusted for sex, age(continuous), smoker versus past or never smoker, hypertension, baselineof diabetes, baseline LDL-C level (continuous), baseline HDL-C level(continuous), and antibiotic. §Likelihood ratio test of interactionbetween KIF6 carrier and treatment.

TABLE 8 Genotype event count no event count total count GG 25 134 159 AG119 454 573 AA 83 431 514 carrier 144 588 732

TABLE 9 Group Model* Hazard ratio 95% CI Lower 95% CI Upper p valueCarrier vs noncarrier 1 1.27 0.97 1.66 0.082 2 1.24 0.94 1.62 0.121 31.25 0.95 1.64 0.104 Het vs noncarrier 1 1.36 1.03 1.80 0.033 2 1.331.00 1.75 0.049 3 1.33 1.01 1.77 0.045 Minor hom vs noncarrier 1 0.970.62 1.52 0.911 2 0.95 0.61 1.48 0.816 3 0.97 0.62 1.52 0.896Model 1—unadjustedModel 2—adjusted for age, sex and smoking statusModel 3—adjusted for age, sex, smoking status, history of hypertension,LDL, HDL and history of diabetesEffect of Pravastatin Compared with Placebo on Risk of CHD in PROSPERSubgroups Defined by KIF6 SNP (rs20455) Genotypes (Elderly Population)

TABLE 10 (Placebo arm) genotype event no event total GG 25 134 159 AG119 454 573 AA 83 431 514 carrier 144 588 732

TABLE 11 (Pravastatin arm) genotype event no event total GG 18 156 174AG 85 501 586 AA 80 456 536 carrier 103 657 760

TABLE 12 Hazard 95% 95% Group Model* ratio CI Lower CI Upper p valueminor homozyote 1 0.65 0.35 1.18 0.156 2 0.65 0.35 1.19 0.160 3 0.630.34 1.17 0.143 heterozygote 1 0.67 0.51 0.89 0.005 2 0.67 0.51 0.890.005 3 0.68 0.51 0.90 0.007 major homozyote 1 0.93 0.68 1.26 0.639 20.92 0.68 1.25 0.607 3 0.92 0.68 1.25 0.604 carrier 1 0.67 0.52 0.860.002 2 0.67 0.52 0.86 0.002 3 0.67 0.52 0.87 0.002Model 1—unadjustedModel 2—adjusted for age, sex and smoking statusModel 3—adjusted for age, sex, smoking status, history of hypertension,LDL, HDL and history of diabetes

TABLE 13 p_model1 p_model2 p_model3 Interaction between 0.1002030450.108490165 0.122604071 carrier status and treatment Interaction betweenhet 0.123178705 0.129901043 0.150787067 vs noncarrier and treatment

TABLE 14 Association of SNPs in the KIF6 fine-mapping region with CHD,particularly MI and RMI Genotype in CARE CARE WOSCOPS Case Control rshCV r2^(a) Risk^(b) p value^(b) Model^(c) Risk^(b) p value^(b) Model^(c)Genot Count Count rs20455 hCV3054799 original 1.66 0.010 Heterozygote1.65 0.002 Heterozygote AA 44 495 hit rs9462535 hCV3054808 0.814 1.630.014 Heterozygote 1.57 0.004 Dominant CC 44 494 rs9471077 hCV30548130.797 1.77 0.006 Heterozygote 1.51 0.008 Dominant TT 38 450 rs9394584hCV30225864 0.797 1.42 0.055 Dominant 1.52 0.007 Heterozygote TT 55 564rs11755763 hCV3054809 0.402 1.47 0.126 Recessive 1.37 0.101 Recessive GG45 363 rs9471080 hCV29992177 0.364 1.65 0.012 Heterozygote 1.29 0.149Heterozygote AA 77 751 Genotype in CARE Genotype in WOSCOPS Case ControlCase Control Case Control Case Control rs Genot Count Count Genot CountCount Genot Count Count Genot Count Count rs20455 GA 81 548 GG 16 138 TT104 256 CT 137 204 rs9462535 AC 81 559 AA 18 174 CC 96 228 AC 141 213rs9471077 CT 78 521 CC 18 172 TT 94 231 CT 136 218 rs9394584 CT 68 492CC 14 99 TT 128 290 CT 125 186 rs11755763 AG 75 571 AA 20 229 GG 83 144AG 145 264 rs9471080 GA 47 278 GG 2 31 AA 185 371 GA 72 112 Genotype inWOSCOPS Case Control Meta-Analysis^(d) rs Genot Count Count p value RiskModel rs20455 CC 35 59 0.000047 1.659509397 Heterozygote rs9462535 AA 4366 0.000348 1.577165825 Heterozygote rs9471077 CC 39 66 0.0001551.626493396 Heterozygote rs9394584 CC 22 43 0.001318 1.476188836Heterozygote rs11755763 AA 46 113 0.025282 0.709869659 Recessivers9471080 GG 3 12 0.006167 1.435129278 Heterozygote The risk estimateand p value were calculated by logistic regression among placebo-treatedpatients ^(a)R2 with hCV3054799 based on CARE placebo-treated patients.^(b)The risk estimate and p value was from either the genotypic orgenetic models (additive, dominant, recessive) which gave the lowest pvalue. ^(c)Genetic model which the risk estimate and the p value werecalculated ^(d)The risk estimate and p value was from either thegenotypic or genetic models (additive, dominant, recessive) which gavethe lowest p value in combined CARE and WOSCOPS.

TABLE 15 GLM GLM Ref Case Control Non-Ref hCV rs number model P valueOddsRatio OR95l OR95u Allele Freq Freq Allele hCV3054805 rs2894424 GC0.051808295 1.482242 0.99692 2.203829 C 0.566434 0.5846906 G hCV3054808rs9462535 AC 0.013593462 1.62685 1.105336 2.394422 C 0.590909 0.6303993A hCV3054808 rs9462535 dominant 0.028697195 1.516371 1.044277 2.201888 C0.590909 0.6303993 A hCV3054822 rs11751357 AA 0.008349315 2.3382461.243867 4.395482 T 0.65035 0.7597561 A hCV3054822 rs11751357 AT0.000134125 2.045113 1.416585 2.952513 T 0.65035 0.7597561 A hCV3054822rs11751357 dominant 4.46E−05 2.087719 1.466207 2.972685 T 0.650350.7597561 A hCV3054822 rs11751357 additive 7.23E−05 1.698221 1.30742.20587 T 0.65035 0.7597561 A hCV3054822 rs11751357 recessive0.092804388 1.671318 0.918227 3.042062 T 0.65035 0.7597561 A hCV3054829rs4535541 CC 0.088634233 0.621377 0.359319 1.074558 T 0.597902 0.5461601C hCV3054829 rs4535541 additive 0.084241704 0.795789 0.614026 1.031356 T0.597902 0.5461601 C hCV31340487 rs12175497 dominant 0.0832731590.592614 0.32782 1.07129 T 0.954545 0.9241181 C hCV31340487 rs12175497additive 0.066496869 0.584648 0.329551 1.037209 T 0.954545 0.9241181 ChCV792699 rs728218 CC 0.093985146 1.536276 0.929485 2.539196 T 0.5244760.5771429 C hCV792699 rs728218 additive 0.086254401 1.242667 0.9695141.592778 T 0.524476 0.5771429 C Case Control Case Case Control ControlCase Case hCV Freq Freq Genot Count Freq Count Freq Genot Count FreqhCV3054805 0.433566 0.4153094 CC 41 0.286713 433 0.3526059 GC 800.559441 hCV3054808 0.409091 0.3696007 CC 44 0.307692 494 0.402608 AC 810.566434 hCV3054808 0.409091 0.3696007 CC 44 0.307692 494 0.402608 AC 810.566434 hCV3054822 0.34965 0.2402439 TT 57 0.398601 714 0.5804878 AT 720.503497 hCV3054822 0.34965 0.2402439 TT 57 0.398601 714 0.5804878 AT 720.503497 hCV3054822 0.34965 0.2402439 TT 57 0.398601 714 0.5804878 AT 720.503497 hCV3054822 0.34965 0.2402439 TT 57 0.398601 714 0.5804878 AT 720.503497 hCV3054822 0.34965 0.2402439 TT 57 0.398601 714 0.5804878 AT 720.503497 hCV3054829 0.402098 0.4538399 TT 48 0.335664 343 0.2802288 CT75 0.524476 hCV3054829 0.402098 0.4538399 TT 48 0.335664 343 0.2802288CT 75 0.524476 hCV31340487 0.045455 0.0758819 TT 130 0.909091 10430.8556194 CT 13 0.090909 hCV31340487 0.045455 0.0758819 TT 130 0.9090911043 0.8556194 CT 13 0.090909 hCV792699 0.475524 0.4228571 TT 380.265734 403 0.3289796 CT 74 0.517483 hCV792699 0.475524 0.4228571 TT 380.265734 403 0.3289796 CT 74 0.517483 Control Control Case Case ControlControl hCV Count Freq Genot Count Freq Count Freq hCV3054805 5700.4641694 GG 22 0.153846 225 0.1832248 hCV3054808 559 0.4555827 AA 180.125874 174 0.1418093 hCV3054808 559 0.4555827 AA 18 0.125874 1740.1418093 hCV3054822 441 0.3585366 AA 14 0.097902 75 0.0609756hCV3054822 441 0.3585366 AA 14 0.097902 75 0.0609756 hCV3054822 4410.3585366 AA 14 0.097902 75 0.0609756 hCV3054822 441 0.3585366 AA 140.097902 75 0.0609756 hCV3054822 441 0.3585366 AA 14 0.097902 750.0609756 hCV3054829 651 0.5318627 CC 20 0.13986 230 0.1879085hCV3054829 651 0.5318627 CC 20 0.13986 230 0.1879085 hCV31340487 1670.1369975 CC 0 0 9 0.0073831 hCV31340487 167 0.1369975 CC 0 0 90.0073831 hCV792699 608 0.4963265 CC 31 0.216783 214 0.1746939 hCV792699608 0.4963265 CC 31 0.216783 214 0.1746939 OR95l = lower 95% confidenceinterval for the Odds Ratio OR95lu = upper 95% confidence interval forthe Odds Ratio GLM = Generalize Linear Model

TABLE 16 total count ALL ALL case control case control case MarkerStrata (ALL) Allele frq Allele frq Genot count count Genot count countGenot count hCV15876373 ALL 2777 C 0.106 T 0.8945 C C 4 28 C T 43 479 TT 204 hCV15876373 placebo 1369 C 0.102 T 0.8977 C C 0 13 C T 23 231 T T120 hCV15876373 statin 1408 C 0.109 T 0.8913 C C 4 15 C T 20 248 T T 84hCV1650850 ALL 2779 G 0.007 C 0.993 G G 0 0 G C 3 36 C C 248 hCV1650850placebo 1369 G 0.007 C 0.9934 G G 0 0 G C 1 17 C C 141 hCV1650850 statin1410 G 0.007 C 0.9926 G G 0 0 G C 2 19 C C 107 hCV29649182 ALL 2781 T0.134 C 0.8664 T T 3 53 T C 69 562 C C 179 hCV29649182 placebo 1371 T0.14 C 0.8596 T T 1 25 T C 41 292 C C 101 hCV29649182 statin 1410 T0.127 C 0.873 T T 2 28 T C 28 270 C C 78 hCV30388472 ALL 2763 C 0.459 T0.5413 C C 48 539 C T 124 1237 T T 75 hCV30388472 placebo 1363 C 0.464 T0.5363 C C 31 254 C T 75 619 T T 35 hCV30388472 statin 1400 C 0.454 T0.5461 C C 17 285 C T 49 618 T T 40 hCV30478067 ALL 2781 A 0.065 G0.9351 A A 3 12 A G 24 307 G G 225 hCV30478067 placebo 1370 A 0.065 G0.935 A A 0 5 A G 16 152 G G 127 hCV30478067 statin 1411 A 0.065 G0.9352 A A 3 7 A G 8 155 G G 98 hCV3054766 ALL 2782 A 0.499 C 0.5007 A A54 647 A C 130 1246 C C 67 hCV3054766 placebo 1370 A 0.499 C 0.5011 A A35 296 A C 75 630 C C 32 hCV3054766 statin 1412 A 0.5 C 0.5004 A A 19351 A C 55 616 C C 35 hCV3054789 ALL 2766 A 0.332 T 0.6676 A A 32 267 AT 120 1121 T T 98 hCV3054789 placebo 1364 A 0.331 T 0.669 A A 14 123 A T69 560 T T 58 hCV3054789 statin 1402 A 0.334 T 0.6662 A A 18 144 A T 51561 T T 40 hCV3054805 ALL 2779 G 0.413 C 0.5867 G G 42 446 G C 129 1192C C 81 hCV3054805 placebo 1371 G 0.417 C 0.5828 G G 22 225 G C 80 570 CC 41 hCV3054805 statin 1408 G 0.409 C 0.5906 G G 20 221 G C 49 622 C C40 hCV3054808 ALL 2778 A 0.38 C 0.6197 A A 39 369 A C 125 1172 C C 88hCV3054808 placebo 1370 A 0.374 C 0.6263 A A 18 174 A C 81 559 C C 44hCV3054808 statin 1408 A 0.387 C 0.6133 A A 21 195 A C 44 613 C C 44hCV3054822 ALL 2782 A 0.255 T 0.7451 A A 27 159 A T 111 935 T T 114hCV3054822 placebo 1373 A 0.252 T 0.7484 A A 14 75 A T 72 441 T T 57hCV3054822 statin 1409 A 0.258 T 0.742 A A 13 84 A T 39 494 T T 57hCV3054829 ALL 2778 C 0.455 T 0.5455 C C 41 500 C T 133 1310 T T 78hCV3054829 placebo 1367 C 0.448 T 0.5516 C C 20 230 C T 75 651 T T 48hCV3054829 statin 1411 C 0.46 T 0.5397 C C 21 270 C T 58 659 T T 30hCV31340487 ALL 2767 C 0.074 T 0.9265 C C 1 16 C T 28 345 T T 223hCV31340487 placebo 1362 C 0.073 T 0.9273 C C 0 9 C T 13 167 T T 130hCV31340487 statin 1405 C 0.074 T 0.9256 C C 1 7 C T 15 178 T T 93hCV32202303 ALL 2771 C 0.095 G 0.9054 C C 1 18 C G 35 451 G G 216hCV32202303 placebo 1365 C 0.097 G 0.9029 C C 1 7 C G 22 227 G G 120hCV32202303 statin 1406 C 0.092 G 0.9079 C C 0 11 C G 13 224 G G 96hCV792699 ALL 2772 C 0.435 T 0.5648 C C 60 467 C T 122 1237 T T 69hCV792699 placebo 1368 C 0.428 T 0.5716 C C 31 214 C T 74 608 T T 38hCV792699 statin 1404 C 0.442 T 0.558 C C 29 253 C T 48 629 T T 31hCV3054799 ALL 2677 G 0.36 A 0.6401 G G 34 308 G A 127 1116 A A 83hCV3054799 placebo 1322 G 0.354 A 0.6456 G G 16 138 G A 81 548 A A 44hCV3054799 statin 1355 G 0.365 A 0.6347 G G 18 170 G A 46 568 A A 39Minor Homozygotes + Heterozygotes (i.e., carriers of at least MinorHomozygotes one copy of minor allele) OR for Heterozygotes OR forcontrol minor 95% 95% OR for 95% 95% carrier 95% Marker count hom CI_LCI_U p Het CI_L CI_U p (Min + Het) CI_L hCV15876373 2019 hCV15876373 982N/A N/A N/A 0.128 0.8241 0.46414 1.46336 0.528 0.9708 0.56171hCV15876373 1037 hCV1650850 2492 hCV1650850 1210 N/A N/A N/A 1 1.71430.16906 17.3826 1 1.7143 0.16906 hCV1650850 1282 hCV29649182 1915hCV29649182 911 1.7333 0.16658 18.0364  1 0.7631 0.48447 1.2021 0.2530.7818 0.50151 hCV29649182 1004 hCV30388472 740 hCV30388472 349 0.51750.29298 0.91415 0.024 0.6798 0.48192 0.95887 0.03 0.6291 0.46873hCV30388472 391 hCV30478067 2210 hCV30478067 1070 N/A N/A N/A 0.5050.5153 0.22677 1.17112 0.138 0.6875 0.32861 hCV30478067 1140 hCV3054766638 hCV3054766 302 0.4856 0.28343 0.83209 0.01 0.7705 0.55309 1.073340.14 0.6695 0.50506 hCV3054766 336 hCV3054789 1128 hCV3054789 540 1.08730.56177 2.10445 0.853 0.7597 0.53833 1.072 0.125 0.8227 0.6075hCV3054789 588 hCV3054805 889 hCV3054805 433 0.9317 0.52221 1.662380.872 0.5933 0.42282 0.8326 0.002 0.6653 0.49722 hCV3054805 456hCV3054808 985 hCV3054808 494 1.037  0.56982 1.88734 1 0.5292 0.372680.75132 3E−04 0.6257 0.46442 hCV3054808 491 hCV3054822 1436 hCV3054822714 0.852  0.42395 1.71219 0.682 0.5213 0.35998 0.75503 4E−04 0.57780.41718 hCV3054822 722 hCV3054829 716 hCV3054829 343 0.9021 0.500741.62503 0.747 0.783 0.56474 1.08572 0.146 0.8052 0.60541 hCV3054829 373hCV31340487 2154 hCV31340487 1043 N/A N/A N/A 0.471 1.0761 0.526752.19848 1 1.1573 0.57217 hCV31340487 1111 hCV32202303 2050 hCV32202303988 N/A N/A N/A 0.421 0.6208 0.32018 1.2038 0.164 0.5857 0.30354hCV32202303 1062 hCV792699 817 hCV792699 403 0.8127 0.50466 1.308910.412 0.6534 0.4617 0.9248 0.017 0.7089 0.53582 hCV792699 414 hCV30547991009 hCV3054799 495 0.9215 0.48648 1.7457  0.857 0.5818 0.41229 0.820930.002 0.6442 0.47726 hCV3054799 514 Minor Homozygotes + Heterozygotes(i.e., carriers of at least Major Homozygotes one copy of minor allele)OR for 95% major 95% 95% HW(ALL) Marker CI_U p hom CI_L CI_U p pExactBDpvalue hCV15876373 0.84 hCV15876373 1.67771 1 0.6881 0.52734 0.897970.006 0.883 0.0989 hCV15876373 0.492 0.0989 hCV1650850 1 hCV165085017.3826 1 0.7381 0.58069 0.9382 0.014 1 hCV1650850 1 hCV29649182 0.287hCV29649182 1.21872 0.319 0.7223 0.54442 0.95834 0.028 0.911 0.692hCV29649182 0.0913 0.692 hCV30388472 0.674 hCV30388472 0.84425 0.0021.0182 0.66085 1.56888 1 0.414 0.0511 hCV30388472 0.146 0.0511hCV30478067 0.276 hCV30478067 1.43835 0.423 0.7461 0.58032 0.95923 0.0251 0.675 hCV30478067 0.0781 0.675 hCV3054766 0.57 hCV3054766 0.887470.005 0.9847 0.62409 1.55359 1 0.305 0.0504 hCV3054766 0.0626 0.0504hCV3054789 0.578 hCV3054789 1.11423 0.232 0.6567 0.44599 0.967 0.0350.142 0.217 hCV3054789 0.509 0.217 hCV3054805 0.309 hCV3054805 0.890320.006 0.9323 0.61443 1.41473 0.817 0.374 0.675 hCV3054805 0.582 0.675hCV3054808 0.629 hCV3054808 0.84308 0.002 1.0056 0.67383 1.50075 1 0.9540.497 hCV3054808 0.537 0.497 hCV3054822 0.583 hCV3054822 0.80021 8E−040.9897 0.6951 1.40925 1 0.774 0.125 hCV3054822 0.676 0.125 hCV30548290.0129 hCV3054829 1.07087 0.153 0.6064 0.39272 0.93632 0.024 0.007370.282 hCV3054829 0.422 0.282 hCV31340487 0.575 hCV31340487 2.34076 0.7040.697 0.54076 0.89829 0.006 0.422 0.125 hCV31340487 0.847 0.125hCV32202303 0.223 hCV32202303 1.13025 0.121 0.7655 0.59291 0.98822 0.0450.164 0.378 hCV32202303 0.874 0.378 hCV792699 0.877 hCV792699 0.93780.016 0.8085 0.51256 1.27518 0.382 0.544 0.962 hCV792699 0.417 0.962hCV3054799 0.706 hCV3054799 0.86943 0.005 0.8639 0.57082 1.30753 0.4960.167 0.717 hCV3054799 0.412 0.717 N/A indicates that a value could notbe calculated because at least one of the strata had a 0 count for minorhomozygotes in cases and/or controls OR = Odds ratio 95% CI_L = Lower95% confidence interval 95% CI_U = upper 95% confidence intervalHW(ALL)pExact = Hardy-Weinberg expectations using an exact test BDpvalue= Breslow-Day p-value

TABLE 17 Patients with Aneurysm or Dissection vs Control (555 cases and180 controls) Genotypic results OR (min hom OR (het Count Count CountRisk ALL Case Control vs maj vs maj Marker Gene (ALL) (cases) (controls)allele frq frq frq hom) P value hom) hCV3054799 KIF6 735 555 180 G 0.3850.4009 0.3361 1.68 0.06 1.36 Allelic results Genotypic results allelicAOR OR sc OR95CI OR95CI Marker P value (Dom) P value (Rec) P value pExactOR lower upper hCV3054799 0.12 1.43 0.04 1.43 0.19 0.029 1.32 1.0299 1.7

TABLE 18 Patients with Dissection vs Control (128 cases and 180controls) Genotypic results OR (Min hom OR (het Count Count Count RiskALL Case Control vs maj vs maj Marker Gene (ALL) (cases) (controls)allele frq frq frq hom) P value hom) hCV3054799 KIF6 308 128 180 G0.3701 0.418 0.3361 1.75 0.14 1.81 Allelic results Genotypic resultsallelicA OR OR sc OR95CI OR95CI Marker P value (Dom) P value (Rec) Pvalue pExact OR lower upper hCV3054799 0.02 1.80 0.02 1.25 0.50 0.0421.42 1.0188 1.97frq=frequency“Min” indicates minor allele homozygote“Maj” indicates major allele homozygote“Het” indicates heterozygote“Dom” indicates dominant model (minor homozygote plus heterozygote vsmajor homozygote)“Rec” indicates recessive model (minor homozygote vs heterozygote plusmajor homozygote)

TABLE 19 Genotype Counts in Aneurysm or Dissection Endpoint HW CaseControl Case Control Case Control (Control) Marker Endpoint Genot cntcnt Genot cnt cnt Genot cnt cnt pExact hCV3054799 Aneurysm G G 92 22 G A261 77 A A 202 81 0.616 or Dissection

TABLE 20 Genotype Counts in Dissection Endpoint HW Case Control CaseControl Case Control (Control) Marker Endpoint Genot cnt cnt Genot cntcnt Genot cnt cnt pExact hCV3054799 Dissection G G 19 22 G A 69 77 A A40 81 0.616

TABLE 21 Odds Case Control Endpoint hCV Model P Value Ratio OR95l OR95uGenotype Count Count Dissection hCV3054799 GA 0.009 2.77 1.29 5.97 AA 2529 Dissection hCV3054799 GG 0.637 1.27 0.48 3.36 AA 25 29 DissectionhCV3054799 dominant 0.027 2.20 1.09 4.43 AA 25 29 Dissection hCV3054799additive 0.231 1.34 0.83 2.18 AA 25 29 Dissection hCV3054799 recessive0.538 0.75 0.31 1.85 AA 25 29 Aneurysm or hCV3054799 GA 0.046 1.91 1.013.59 AA 131 29 dissection Aneurysm or hCV3054799 GG 0.907 1.05 0.49 2.25AA 131 29 dissection Aneurysm or hCV3054799 dominant 0.109 1.58 0.902.76 AA 131 29 dissection Aneurysm or hCV3054799 additive 0.448 1.170.78 1.74 AA 131 29 dissection Aneurysm or hCV3054799 recessive 0.4920.78 0.38 1.60 AA 131 29 dissection Case Control Case Control TotalTotal Endpoint Genotype Count Count Genotype Count Count Cases ControlsDissection GA 43 18 GG 12 11 80 58 Dissection GA 43 18 GG 12 11 80 58Dissection GA 43 18 GG 12 11 80 58 Dissection GA 43 18 GG 12 11 80 58Dissection GA 43 18 GG 12 11 80 58 Aneurysm or GA 155 18 GG 52 11 338 58dissection Aneurysm or GA 155 18 GG 52 11 338 58 dissection Aneurysm orGA 155 18 GG 52 11 338 58 dissection Aneurysm or GA 155 18 GG 52 11 33858 dissection Aneurysm or GA 155 18 GG 52 11 338 58 dissection AAgenotype was used as reference “OR95l” = lower 95% confidence intervalfor the odds ratio “OR95u” = upper 95% confidence interval for the oddsratio

TABLE 22 Effect of pravastatin on MI and CHD: CARE and WOSCOPS GenotypeCounts Case Control Case Control Case Study Subgroup HCV Genotype CountCount Genotype Count Count Genotype Count CARE Pravastatin hCV3054808 CC44 491 AC 44 613 AA 21 CARE Placebo hCV3054808 CC 44 494 AC 81 559 AA 18WOSCOPS Pravastatin hCV3054808 CC 72 193 AC 83 248 AA 28 WOSCOPS PlacebohCV3054808 CC 94 224 AC 134 207 AA 39 CARE Pravastatin hCV29992177 AA 58798 GA 27 281 GG 4 CARE Placebo hCV29992177 AA 77 751 GA 47 278 GG 2WOSCOPS Pravastatin hCV29992177 AA 125 354 GA 51 148 GG 7 WOSCOPSPlacebo hCV29992177 AA 185 371 GA 72 112 GG 3 CARE PravastatinhCV30225864 TT 43 604 CT 44 503 CC 13 CARE Placebo hCV30225864 TT 55 564CT 68 492 CC 14 WOSCOPS Pravastatin hCV30225864 TT 89 260 CT 85 234 CC16 WOSCOPS Placebo hCV30225864 TT 128 290 CT 125 186 CC 22 CAREPravastatin hCV3054813 TT 40 448 CT 38 570 CC 19 CARE Placebo hCV3054813TT 38 450 CT 78 521 CC 18 WOSCOPS Pravastatin hCV3054813 TT 76 196 CT 82258 CC 31 WOSCOPS Placebo hCV3054813 TT 94 231 CT 136 218 CC 39 GenotypeCounts Control Effect of Pravastatin on MI and CHD Study Subgroup HCVCount Genotype OR 95% CI p value Genotype OR CARE Pravastatin hCV3054808195 CC 1.01 0.65-1.55 1.00000 AC 0.50 CARE Placebo hCV3054808 174WOSCOPS Pravastatin hCV3054808 83 CC 0.89 0.61-1.27 0.58041 AC 0.52WOSCOPS Placebo hCV3054808 64 CARE Pravastatin hCV29992177 33 AA 0.710.50-1.01 0.05971 GA 0.57 CARE Placebo hCV29992177 31 WOSCOPSPravastatin hCV29992177 11 AA 0.71 0.54-0.93 0.01422 GA 0.54 WOSCOPSPlacebo hCV29992177 12 CARE Pravastatin hCV30225864 117 TT 0.730.48-1.11 0.14200 CT 0.63 CARE Placebo hCV30225864 99 WOSCOPSPravastatin hCV30225864 47 TT 0.78 0.56-1.07 0.12642 CT 0.54 WOSCOPSPlacebo hCV30225864 43 CARE Pravastatin hCV3054813 186 TT 1.06 0.67-1.680.81479 CT 0.45 CARE Placebo hCV3054813 172 WOSCOPS PravastatinhCV3054813 82 TT 0.95 0.67-1.36 0.85556 CT 0.51 WOSCOPS PlacebohCV3054813 66 Effect of Pravastatin on MI and CHD Study Subgroup HCV 95%CI p value Genotype OR 95% CI p value CARE Pravastatin hCV30548080.33-0.72 0.00032 AA 1.04 0.53-2.01 1.00000 CARE Placebo hCV3054808WOSCOPS Pravastatin hCV3054808 0.37-0.71 0.00010 AA 0.55 0.3-0.990.05540 WOSCOPS Placebo hCV3054808 CARE Pravastatin hCV299921770.34-0.94 0.02648 GG 1.88 0.32-10.99 0.67667 CARE Placebo hCV29992177WOSCOPS Pravastatin hCV29992177 0.35-0.83 0.00608 GG 2.55 0.52-12.370.28280 WOSCOPS Placebo hCV29992177 CARE Pravastatin hCV302258640.42-0.94 0.02803 CC 0.79 0.35-1.75 0.68302 CARE Placebo hCV30225864WOSCOPS Pravastatin hCV30225864 0.39-0.76 0.00038 CC 0.67 0.31-1.430.33663 WOSCOPS Placebo hCV30225864 CARE Pravastatin hCV30548130.30-0.67 0.00008 CC 0.98 0.50-1.92 1.00000 CARE Placebo hCV3054813WOSCOPS Pravastatin hCV3054813 0.37-0.71 0.00006 CC 0.64 0.36-1.130.14713 WOSCOPS Placebo hCV3054813 OR = odd ratio 95% CI = 95%confidence interval

TABLE 4 Interrogated SNP Interrogated rs LD SNP LD SNP rs PowerThreshold r² r² hCV29992177 rs9471080  hCV29576755 rs6899653 0.510.524353992 0.55894 hCV29992177 rs9471080  hCV29703356 rs9471079 0.510.524353992 1 hCV29992177 rs9471080  hCV30225864 rs9394584 0.510.524353992 0.54118 hCV30225864 rs9394584  hCV29161261 rs6924090 0.510.604351053 0.88462 hCV30225864 rs9394584  hCV2946524  rs20456  0.510.604351053 0.62838 hCV30225864 rs9394584  hCV29576755 rs6899653 0.510.604351053 1 hCV30225864 rs9394584  hCV30280062 rs7772430 0.510.604351053 0.64299 hCV30225864 rs9394584  hCV3054799  rs20455  0.510.604351053 0.85135 hCV30225864 rs9394584  hCV3054805  rs2894424 0.510.604351053 0.67391 hCV30225864 rs9394584  hCV3054813  rs9471077 0.510.604351053 0.66022 hCV3054799  rs20455   hCV29161261 rs6924090 0.510.905231457 1 hCV3054822  rs11751357 hCV11606396 rs1887716 0.510.202258224 0.4381 hCV3054822  rs11751357 hCV26547610 rs5006081 0.510.202258224 0.26881 hCV3054822  rs11751357 hCV27495641 rs3823213 0.510.202258224 0.66707 hCV3054822  rs11751357 hCV27505675 rs3818308 0.510.202258224 0.27141 hCV3054822  rs11751357 hCV29161257 rs6904582 0.510.202258224 0.4381 hCV3054822  rs11751357 hCV29161258 rs6901022 0.510.202258224 0.65497 hCV3054822  rs11751357 hCV29902034 rs9380848 0.510.202258224 0.66707 hCV3054822  rs11751357 hCV29937959 rs9462531 0.510.202258224 0.41097 hCV3054822  rs11751357 hCV30082078 rs7774204 0.510.202258224 0.38155 hCV3054822  rs11751357 hCV30190183 rs7774046 0.510.202258224 0.38155 hCV3054822  rs11751357 hCV30478066 rs9462533 0.510.202258224 0.54264 hCV3054822  rs11751357 hCV30532403 rs7754225 0.510.202258224 0.38155 hCV3054822  rs11751357 hCV30586596 rs9369112 0.510.202258224 0.63465 hCV3054822  rs11751357 hCV792698  rs728217  0.510.202258224 0.37822 hCV3054822  rs11751357 hCV8948890  rs1328384 0.510.202258224 0.26881 hCV3054822  rs11751357 hDV70715992  rs16891930 0.510.202258224 0.59752 hCV3054822  rs11751357 hDV70716012  rs16891961 0.510.202258224 0.25712 hCV32202303 rs11751690 hCV1416391   rs11751730 0.510.668241315 0.77328 hCV32202303 rs11751690 hCV1416399   rs11752840 0.510.668241315 0.82307 hCV32202303 rs11751690 hCV16029234 rs2499452 0.510.668241315 0.82307 hCV32202303 rs11751690 hCV1703050  rs2499450 0.510.668241315 0.82293 hCV32202303 rs11751690 hCV2487638   rs11758101 0.510.668241315 0.88 hCV32202303 rs11751690 hCV2487644   rs11754132 0.510.668241315 1 hCV32202303 rs11751690 hCV3078072  rs303675  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV3078083  rs302593  0.510.668241315 0.82293 hCV32202303 rs11751690 hCV3078087   rs11754307 0.510.668241315 0.82307 hCV32202303 rs11751690 hCV32203040  rs11755914 0.510.668241315 0.75058 hCV32202303 rs11751690 hCV814553  rs302573  0.510.668241315 0.82293 hCV32202303 rs11751690 hCV814557  rs302575  0.510.668241315 0.82259 hCV32202303 rs11751690 hCV814585  rs160023  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814588  rs159958  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814594  rs302596  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814600  rs302588  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814607  rs303701  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814610  rs159957  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814619  rs303693  0.510.668241315 0.80889 hCV32202303 rs11751690 hCV814621  rs303653  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV814633  rs303649  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV8948950  rs964116  0.510.668241315 0.82307 hCV32202303 rs11751690 hCV8948982  rs303678  0.510.668241315 0.90035 hCV32202303 rs11751690 hDV71111070 rs302595  0.510.668241315 0.82307

1-7. (canceled)
 8. A method for identifying a human who is in need ofreceiving treatment for CHD or aneurysm/dissection, comprising detectinga SNP as specified in any one of the nucleic acid sequences of SEQ IDNOS:1 and 3-132, in a sample from said human, and treating said humanwith a therapeutic agent.
 9. The method of claim 8 wherein saidtherapeutic agent is selected from the group consisting of chemicalentities and antibodies.
 10. The method of claim 8, wherein thetherapeutic agent is a statin. 11-12. (canceled)
 13. A method fordetermining an individual's risk for a cardiovascular event, the methodcomprising determining which allele is present at at least one SNPselected from the group consisting of rs20455, rs2894424, rs9462535,rs11751357, rs4535541, rs12175497, rs728218, rs2281686, rs35268572,rs9471032, rs9357303, rs9471078, rs9394587, rs4711595, rs11751690,rs9471077, rs9394584, rs11755763, and rs9471080, wherein the presence ofthe allele is indicative of an altered risk for the cardiovascularevent.
 14. The method of claim 13, wherein the altered risk is anincreased risk.
 15. The method of claim 13, wherein the altered risk isa decreased risk.
 16. The method of claim 13, wherein the cardiovascularevent is a coronary event.
 17. The method of claim 16, wherein thecoronary event is selected from the group consisting of CHD, aneurysm,and dissection.
 18. The method of claim 17, wherein the coronary eventis CHD, and further wherein the CHD is MI. 19-20. (canceled)
 21. Amethod for predicting an individual's response to a drug treatment, themethod comprising determining which allele is present at at least oneSNP selected from the group consisting of rs20455, rs2894424, rs9462535,rs11751357, rs4535541, rs12175497, rs728218, rs2281686, rs35268572,rs9471032, rs9357303, rs9471078, rs9394587, rs4711595, rs11751690,rs9471077, rs9394584, rs11755763, and rs9471080, wherein the presence ofthe allele is indicative of an altered response to the drug treatment.22. The method of claim 21, wherein the drug treatment comprises statintreatment.
 23. The method of claim 22, wherein the statin is selectedfrom the group consisting of pravastatin and atorvastatin.
 24. Themethod of claim 22, wherein the statin is selected from the groupconsisting of fluvastatin, lovastatin, rosuvastatin, and simvastatin.25. The method of claim 22, wherein the statin treatment comprises astatin in combination with at least one additional therapeutic agent.26. The method of claim 25, wherein the statin treatment is selectedfrom the group consisting of: simvastatin in combination with ezetimibe;lovastatin in combination with niacin extended-release; and atorvastatinin combination with amlodipine besylate. 27-28. (canceled)
 29. Themethod of claim 22, wherein the statin treatment is for the preventionor treatment of CHD, aneurysm/dissection, or cancer.
 30. The method ofclaim 13, further comprising providing a report of the individual's riskfor the cardiovascular event based on the allele present at the SNP. 31.The method of claim 21, further comprising providing a report of theindividual's response to the drug treatment based on the allele presentat the SNP.
 32. The method of claim 31, further comprising transmittingthe report to the individual or to a medical practitioner.